Search Results (6,593)

With its unique climate and geographical advantages, Yunnan Province in China has become one of the country’s most important citrus-growing regions. However, the dense foliage and large fruit size of citrus trees often result in significant occlusion, and the fluctuating light intensity further complicates accurate assessment of fruit maturity. To address these challenges, this study proposes an improved model based on YOLOv8, named ORD-YOLO, for citrus fruit maturity detection. To enhance the model’s robustness in complex environments, several key improvements have been introduced. First, the standard convolution operations are replaced with Omni-Dimensional Dynamic Convolution (ODConv) to improve feature extraction capabilities. Second, the feature fusion process is optimized and inference speed is increased by integrating a Re-parameterizable Generalized Feature Pyramid Network (RepGFPN). Third, the detection head is redesigned using a Dynamic Head structure that leverages dynamic attention mechanisms to enhance key feature perception. Additionally, the loss function is optimized using InnerDIoU to improve object localization accuracy. Experimental results demonstrate that the enhanced ORD-YOLO model achieves a precision of 93.83%, a recall of 91.62%, and a mean Average Precision (mAP) of 96.92%, representing improvements of 4.66%, 3.3%, and 3%, respectively, over the original YOLOv8 model. ORD-YOLO not only maintains stable and accurate citrus fruit maturity recognition under complex backgrounds, but also significantly reduces misjudgment caused by manual assessments. Furthermore, the model enables real-time, non-destructive detection. When deployed on harvesting robots, it can substantially increase picking efficiency and reduce post-maturity fruit rot due to delayed harvesting. These advancements contribute meaningfully to the quality improvement, efficiency enhancement, and digital transformation of the citrus industry. Full article

In arid regions with limited water resources, improving cropland water-use efficiency (WUEc) is crucial for maintaining crop production. This study aims to investigate how changes in meteorological and vegetation factors affect WUEc in drylands and to identify its primary drivers, which are essential for understanding how cropland ecosystems respond to complex environmental changes. Using remote sensing data, we analyzed the spatiotemporal patterns of WUEc in Xinjiang from 2002 to 2022 by applying STL decomposition, Sen’s slope combined with the Mann–Kendall test, and an XGBoost–SHAP model, quantifying its key controlling factors. The results indicate that from 2002 to 2022, WUEc in Xinjiang showed an overall declining trend. Prior to 2007, WUEc increased at 0.05 gC·m⁻¹·m⁻²·a⁻¹, after which it fluctuated downward at −0.01 gC·m⁻¹·m⁻²·a⁻¹. Intra-annual peaks consistently occurred in May and during September–October. Spatially, WUEc exhibited significant heterogeneity, increasing from south to north, with 53.26% of the region showing declines. Temperature (T) and leaf area index (LAI) emerged as the primary meteorological and vegetation drivers, respectively, influencing WUEc change in 45.7% and 17.6% of the area. Both variables were negatively correlated with WUEc, with negative correlations covering 60% of the region for T and 83% for LAI. These findings provide scientific guidance for optimizing crop structure and water-resource management strategies in arid regions. Full article

 Porcine epidemic diarrhea virus (PEDV) continues to circulate globally, causing substantial economic losses to the swine industry. Historically, PEDV strains are classified into the classical G1, epidemic G2, and S-INDEL genotypes. Among these genotypes, the highly virulent and prevalent G2 genotype has been extensively studied. However, recent clinical outbreaks in China necessitate a reevaluation of the epidemiological and evolutionary dynamics of circulating strains. This study analyzed 37 newly sequenced S genes and public sequences to characterize the genetic variations of S-INDEL strains. Our analysis revealed that S-INDEL strains are endemic throughout China, with a phylogenetic analysis identifying two distinct clades: clade 1, comprising early endemic strains, and clade 2, representing a recently dominant, geographically restricted lineage in China. While inter-genotypic recombination has been documented, our findings also demonstrate that intra-genotypic and intra-clade recombination events contributed significantly to the emergence of clade 2, distinguishing its evolutionary pattern from clade 1. A comparative analysis identified 22 clade-specific amino acid changes, 11 of which occurred in the D0 domain. Notably, mutations at positively selected sites—113 and 114 within the D0 domain, a domain associated with pathogenicity—were specific to clade 2. A phylodynamic analysis indicated Germany as the epicenter of S-INDEL dispersal, with China acting as a sink population characterized by localized transmission networks and frequent recombination events. These results demonstrate that contemporary S-INDEL strains, specifically clade 2, exhibit unique recombination patterns and mutations potentially impacting virulence. Continuous surveillance is essential to assess the pathogenic potential of these evolving recombinant variants and the efficacy of vaccines against them.  Full article

Hydrogen offers an effective pathway for the large-scale storage of renewable energy. For a tourist city located in a plateau region rich in renewable energy, hydrogen shows great potential for reducing carbon emissions and utilizing uncertain renewable energy. Herein, the wind–solar–hydrogen stand-alone and grid-connected systems in the plateau tourist city of Lijiang City in Yunnan Province are modeled and techno-economically evaluated by using the HOMER Pro software (version 3.14.2) with the multi-criteria decision analysis models. The system is composed of 5588 kW solar photovoltaic panels, an 800 kW wind turbine, a 1600 kW electrolyzer, a 421 kWh battery, and a 50 kW fuel cell. In addition to meeting the power requirements for system operation, the system has the capacity to provide daily electricity for 200 households in a neighborhood and supply 240 kg of hydrogen per day to local hydrogen-fueled buses. The stand-alone system can produce 10.15 × 10⁶ kWh of electricity and 93.44 t of hydrogen per year, with an NPC of USD 8.15 million, an LCOE of USD 0.43/kWh, and an LCOH of USD 5.26/kg. The grid-connected system can generate 10.10 × 10⁶ kWh of electricity and 103.01 ton of hydrogen annually. Its NPC is USD 7.34 million, its LCOE is USD 0.11/kWh, and its LCOH is USD 3.42/kg. This study provides a new solution for optimizing the configuration of hybrid renewable energy systems, which will develop the hydrogen economy and create low-carbon-emission energy systems. Full article

Peanut cultivation is widely practiced using plastic mulch film, resulting in the accumulation of microplastics/nanoplastics (MPs/NPs) in agricultural soils, potentially negatively affecting peanut growth. To investigate the effects of two polystyrene (PS) sizes (5 μm, 50 nm) and three concentrations (0, 10, and 100 mg L⁻¹) on peanut growth, photosynthetic efficiency, and physiological characteristics, a 15-day hydroponic experiment was conducted using peanut seedlings as the experimental material. The results indicated that PS-MPs/NPs inhibited peanut growth, reduced soil and plant analyzer development (SPAD) values (6.7%), and increased levels of malondialdehyde (MDA, 22.0%), superoxide anion (O₂⁻, 3.8%) superoxide dismutase (SOD, 16.1%) and catalase (CAT, 12.1%) activity, and ascorbic acid (ASA, 12.6%) and glutathione (GSH, 9.1%) contents compared to the control. Moreover, high concentrations (100 mg L⁻¹) of PS-MPs/NPs reduced the peanut shoot fresh weight (16.1%) and SPAD value (7.2%) and increased levels of MDA (17.1%), O₂⁻ (5.6%), SOD (10.6%), POD (27.2%), CAT (7.3%), ASA (12.3%), and GSH (6.8%) compared to low concentrations (10 mg L⁻¹) of PS-MPs/NPs. Notably, under the same concentration, the impact of 50 nm PS-NPs was stronger than that of 5 μm PS-MPs. The peanut shoot fresh weight of PS-NPs was lower than that of PS-MPs by an average of 7.9%. Additionally, we found that with an increasing exposure time of PS-MPs/NPs, the inhibitory effect of low concentrations of PS-MPs/NPs on the fresh weight was decreased by 2.5%/9.9% (5 d) and then increased by 7.7%/2.7% (15 d). Conversely, high concentrations of PS-MPs/NPs consistently reduced the fresh weight. Correlation analysis revealed a clear positive correlation between peanut biomass and both the SPAD values as well as Fv/Fm, and a negative correlation with MDA, SOD, CAT, ASA, and GSH. Furthermore, the presence of PS-MPs/NPs in roots, stems, and leaves was confirmed using a confocal laser scanning microscope. The internalization of PS-MPs/NPs within peanut tissues negatively impacted peanut growth by increasing the MDA and O₂⁻ levels, reducing the SPAD values, and inhibiting the photosynthetic capacity. In conclusion, the study demonstrated that the effects of PS on peanuts were correlated with the PS size, concentration, and exposure time, highlighting the potential risk of 50 nm to 5 μm PS being absorbed by peanuts. Full article

When faults occur in transmission lines of grid-forming PV systems, the LVRT control and virtual impedance function cause the fault characteristics of grid-forming inverters to differ significantly from those of synchronous generators, which deteriorates the performance of existing protection schemes. To address this issue, this paper analyzes the fault characteristics of PV transmission lines under grid-forming control objectives and the adaptability of traditional current differential protection. Subsequently, a novel pilot protection based on the Jensen–Shannon distance is proposed for transmission line of grid-forming PV systems. Initially, the post-fault current samples are modeled as discrete probability distributions. The Jensen–Shannon distance algorithm quantifies the similarity between the distributions on both line ends. Based on the calculated distance results, internal and external faults are distinguished, optimizing the performance of traditional waveform-similarity-based pilot protection. Simulation results verify that the proposed protection reliably identifies internal and external faults on the protected line. It demonstrates satisfactory performance across different fault resistances and fault types, and exhibits strong noise immunity and synchronization error tolerance. In addition, the proposed pilot protection is compared with the existing waveform-similarity-based protection schemes. Full article

Selenium (Se) is an essential trace element critical for animal growth and immune function. This study investigated the dietary selenium requirement of juvenile large yellow croaker (Larimichthys crocea) through an 8-week feeding trial. Five experimental diets were formulated by supplementing a basal diet with selenium polysaccharides (Se-PS) at 0, 20, 30, 40, and 50 mg/kg, resulting in analyzed Se concentrations of 0.35, 0.54, 0.71, 0.93, and 1.11 mg/kg, respectively. The results demonstrated that growth performance and feed efficiency improved with increasing dietary selenium, peaking at 0.93 mg/kg before declining at higher levels. Antioxidant enzyme activities—superoxide dismutase (SOD) and catalase (CAT)—in serum and liver tissues exhibited a dose-dependent increase, reaching maximal levels at 1.11 mg/kg. Conversely, malondialdehyde (MDA), a marker of oxidative stress, progressively decreased in both serum and liver, attaining its lowest concentration at 1.11 mg/kg, though this did not differ significantly from the 0.93 mg/kg group (p = 0.056). Tissue selenium accumulation was highest at these optimal dietary levels. Based on the growth performance, oxidative stress response, and tissue selenium retention, the recommended dietary selenium requirement for juvenile large yellow croaker is 0.93 mg/kg. These findings highlight the importance of optimal Se supplementation in aquafeeds to enhance growth and physiological health in farmed fish. Full article

The rapid advancement of underwater wireless communication technologies is critical to unlocking the full potential of marine resource exploration and environmental monitoring. This paper reviews recent progress in three primary modalities: underwater acoustic communication, radio frequency (RF) communication, and underwater optical wireless communication (UWOC), each designed to address specific challenges posed by complex underwater environments. Acoustic communication, while effective for long-range transmission, is constrained by ambient noise and high latency; recent innovations in noise reduction and data rate enhancement have notably improved its reliability. RF communication offers high-speed, short-range capabilities in shallow waters, but still faces challenges in hardware miniaturization and accurate channel modeling. UWOC has emerged as a promising solution, enabling multi-gigabit data rates over medium distances through advanced modulation techniques and turbulence mitigation. Additionally, bio-inspired approaches such as electric field communication provide energy-efficient and robust alternatives under turbid conditions. This paper further examines the practical integration of these technologies in underwater platforms, including autonomous underwater vehicles (AUVs), highlighting trade-offs between energy efficiency, system complexity, and communication performance. By synthesizing recent advancements, this review outlines the advantages and limitations of current underwater communication methods and their real-world applications, offering insights to guide the future development of underwater communication systems for robotic and vehicular platforms. Full article

With the development of wave energy, a promising renewable resource, oscillating water column (OWC) devices, has been extensively studied for its potential in harnessing this energy. However, traditional OWC devices face challenges such as corrosion and damage from prolonged exposure to harsh marine environments, limiting their long-term viability and efficiency. To address these limitations, this paper proposes a novel U-tube type dual chamber OWC wave energy conversion device integrated within a marine vehicle. The research involves the design of a U-tube dual-chamber OWC device, which utilizes the pitch motion of a marine vehicle to drive the oscillation of water columns within the U-tube, generating reciprocating airflow that drives an air turbine. Numerical simulations using computational fluid dynamics (CFD) were conducted to analyze the effects of various structural dimensions, including device length, width, air chamber height, U-tube channel width, and bottom channel height, on the aerodynamic power output. The simulations considered real sea conditions, focusing on low-frequency waves prevalent in China’s sea areas. Simulation results reveal that increasing the device’s length and width substantially boosts aerodynamic power, while air chamber height and U-tube channel width have minor effects. These findings provide valuable insights into the optimal design of U-tube dual-chamber OWC devices for efficient wave energy conversion, laying the foundation for future physical prototype development and experimental validation. Full article

Soil salinization is a major constraint to global crop productivity, highlighting the need to identify salt tolerance genes and their molecular mechanisms. Here, we integrated mRNA and miRNA profile analyses to investigate the molecular basis of salt tolerance of an elite Brassica napus cultivar S268. Time-course RNA-seq analysis revealed dynamic transcriptional reprogramming under 215 mM NaCl stress, with 212 core genes significantly enriched in organic acid degradation and glyoxylate/dicarboxylate metabolism pathways. Combined with weighted gene co-expression network analysis (WGCNA) and RT-qPCR validation, five candidate genes (WRKY6, WRKY70, NHX1, AVP1, and NAC072) were identified as the regulators of salt tolerance in rapeseed. Haplotype analysis based on association mapping showed that NAC072, ABI5, and NHX1 exhibited two major haplotypes that were significantly associated with salt tolerance variation under salt stress in rapeseed. Integrated miRNA-mRNA analysis and RT-qPCR identified three regulatory miRNA-mRNA pairs (bna-miR160a/BnaA03.BAG1, novel-miR-126/BnaA08.TPS9, and novel-miR-70/BnaA07.AHA1) that might be involved in S268 salt tolerance. These results provide novel insights into the post-transcriptional regulation of salt tolerance in B. napus, offering potential targets for genetic improvement. Full article

Perfluoroalkyl substances (PFASs) possess immunosuppressive properties. However, their association with rheumatoid arthritis (RA) risk remains inconclusive across epidemiological studies. This study integrates population-based and mechanistic evidence to clarify the relationship between PFAS exposure and RA. We analyzed 8743 U.S. adults from the NHANES (2005–2018), assessing individual and mixed exposures to PFOA, PFOS, PFNA, and PFHxS using multivariable logistic regression, Bayesian kernel machine regression, quantile g-computation, and weighted quantile sum models. Network toxicology and molecular docking were utilized to identify core targets mediating immune disruption. The results showed that elevated PFOA (OR = 1.63, 95% CI: 1.41–1.89), PFOS (OR = 1.41, 1.25–1.58), and PFNA (OR = 1.40, 1.20–1.63) levels significantly increased RA risk. Mixture analyses indicated a positive joint effect (WQS OR = 1.06, 1.02–1.10; qgcomp OR = 1.26, 1.16–1.38), with PFOA as the primary contributor. Stratified analyses revealed stronger effects in females (PFOA Q4 OR = 3.75, 2.36–5.97) and older adults (≥60 years). Core targets included EGFR, SRC, TP53, and CTNNB1. PFAS mixtures increase RA risk, dominated by PFOA and modulated by sex/age. These findings help reconcile prior contradictions by identifying key molecular targets and vulnerable subpopulations, supporting regulatory attention to PFAS mixture exposure. Full article

To improve the efficiency and stability of the system, this paper proposes a monolithic integrated optical path design for a cavity optomechanical accelerometer based on a 250 nm top silicon thickness silicon-on-insulator (SOI) wafer instead of readout through U-shape fiber coupling. Finite Element Analysis (FEA) and Finite-Difference Time-Domain (FDTD) methods are employed to systematically investigate the performance of key optical structures, including the resonant modes and bandgap characteristics of photonic crystal (PhC) microcavities, transmission loss of strip waveguides, coupling efficiency of tapered-lensed fiber-to-waveguide end-faces, coupling characteristics between strip waveguides and PhC waveguides, and the coupling mechanism between PhC waveguides and microcavities. Simulation results demonstrate that the designed PhC microcavity achieves a quality factor (Q-factor) of 2.26 × 10⁵ at a 1550 nm wavelength while the optimized strip waveguide exhibits a low loss of merely 0.2 dB over a 5000 μm transmission length. The strip waveguide to PhC waveguide coupling achieves 92% transmittance at the resonant frequency, corresponding to a loss below 0.4 dB. The optimized edge coupling structure exhibits a transmittance of 75.8% (loss < 1.2 dB), with a 30 μm coupling length scheme (60% transmittance, ~2.2 dB loss) ultimately selected based on process feasibility trade-offs. The total optical path system loss (input to output) is 5.4 dB. The paper confirms that the PhC waveguide–microcavity evanescent coupling method can effectively excite the target cavity mode, ensuring optomechanical coupling efficiency for the accelerometer. This research provides theoretical foundations and design guidelines for the fabrication of high-precision monolithic integrated cavity optomechanical accelerometers. Full article

CT scanners are essential tools in modern medical imaging. Sudden failures of their X-ray tubes can lead to equipment downtime, affecting healthcare services and patient diagnosis. However, existing prediction methods based on a single model struggle to adapt to the multi-stage variation characteristics of tube lifespan and have limited modeling capabilities for temporal features. To address these issues, this paper proposes an intelligent prediction architecture for CT tubes’ remaining useful life based on a dual-branch neural network. This architecture consists of two specialized branches: a residual self-attention BiLSTM (RSA-BiLSTM) and a multi-layer dilation temporal convolutional network (D-TCN). The RSA-BiLSTM branch extracts multi-scale features and also enhances the long-term dependency modeling capability for temporal data. The D-TCN branch captures multi-scale temporal features through multi-layer dilated convolutions, effectively handling non-linear changes in the degradation phase. Furthermore, a dynamic phase detector is applied to integrate the prediction results from both branches. In terms of optimization strategy, a dynamically weighted triplet mixed loss function is designed to adjust the weight ratios of different prediction tasks, effectively solving the problems of sample imbalance and uneven prediction accuracy. Experimental results using leave-one-out cross-validation (LOOCV) on six different CT tube datasets show that the proposed method achieved significant advantages over five comparison models, with an average MSE of 2.92, MAE of 0.46, and R² of 0.77. The LOOCV strategy ensures robust evaluation by testing each tube dataset independently while training on the remaining five, providing reliable generalization assessment across different CT equipment. Ablation experiments further confirmed that the collaborative design of multiple components is significant for improving the accuracy of X-ray tubes remaining life prediction. Full article

To investigate the effect of Botrytis cinerea infection severity on the flavor characteristics of Petit Manseng noble rot wine, this study analyzed wines produced from Petit Manseng grapes grown in the eastern foothills of Helan Mountain, Ningxia, China. The grapes were categorized into three groups based on infection status: uninfected, mildly infected, and severely infected with Botrytis cinerea. Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and an electronic nose were employed to detect and analyze the aroma components of wines under the three infection conditions. Additionally, trained sensory panelists conducted sensory evaluations of the wine aromas. The results revealed that wines made from severely infected grapes exhibited the richest and most complex aroma profiles. A total of 70 volatile compounds were identified, comprising 32 esters, 17 alcohols, 5 acids, 8 aldehydes and ketones, 4 terpenes, and 4 other compounds. Among these, esters and alcohols accounted for the highest contents. Key aroma-active compounds included isoamyl acetate, ethyl decanoate, phenethyl acetate, ethyl laurate, hexanoic acid, linalool, decanoic acid, citronellol, ethyl hexanoate, and methyl octanoate. Sensory evaluation indicated that the “floral aroma”, “pineapple/banana aroma”, “honey aroma”, and “overall aroma intensity” were most pronounced in the severely infected group. These findings provide theoretical support for the harvesting of severely Botrytis cinerea-infected Petit Manseng grapes and the production of high-quality noble rot wine in this region. Full article

SnRK kinases, central regulators of plant stress response, remain uncharacterized in Taxus—an ancient gymnosperm valued for paclitaxel production. This study aimed to identify the Taxus SnRK family and elucidate its functional roles. Specifically, we identified SnRK genes through genomic analysis and assessed tissue-specific expression via transcriptomics, while regulatory networks were deciphered using WGCNA. To overcome experimental constraints, a PEG-mediated protoplast transient expression system was developed using calli, followed by dual-luciferase assays. Consequently, 19 SnRK genes (2 SnRK1, 4 SnRK2, 13 SnRK3) were identified, with tissue-specific expression revealing TaSnRK1.2 upregulation under methyl jasmonate (MeJA) and in stress-resilient tissues (bark/root). Subsequently, WGCNA uncovered a bark/root-specific module containing TaSnRK1.2 with predicted TF interactions (TaGRAS/TaERF). Critically, homologous dual-luciferase assays demonstrated TaSnRK1.2 activates TaGRAS and TaERF promoters (4.34-fold and 3.11-fold induction, respectively). This study establishes the Taxus SnRK family and identifies TaSnRK1.2 as a hub integrating stress signals (e.g., MeJA) to modulate downstream TF networks, while the novel protoplast system enables future functional studies in this medicinal plant. Full article