Search Results (227)

The ten-year fishing ban on the Yangtze River aims to restore aquatic biodiversity and rebuild fishery resources. Megalobrama skolkovii, a key species in the basin, was investigated using 2024 data to provide a preliminary assessment of its population structure, stock dynamics, and early recovery. Age analysis (n = 243) showed that 1–6-year-olds were dominated by fish aged 3 (35%), with few older than 4, indicating moderate structural truncation. Growth parameters modeled by the von Bertalanffy Growth Function yielded L_∞ = 61.89 cm and k = 0.25 year⁻¹, with a weight–growth inflection age of 4.4 years. Natural mortality (M = 0.48 year⁻¹) was estimated using Pauly’s empirical formula, and total mortality (Z = 0.55 year⁻¹) was estimated from the catch curve analysis. While fishing mortality (F) was statistically indistinguishable from zero, a plausible low-intensity fishing scenario was explored to assess potential impacts of residual activities. Length-based indicators (LBIs) showed P_mat = 46.05%, P_opt = 9.51%, and P_mega = 6.88%, suggesting reproductive recovery but incomplete structural restoration. These preliminary findings reveal an asymmetrical recovery trajectory, whereby physiological improvements and enhanced recruitment have occurred, yet full structural restoration remains incomplete. This underscores the need for continued, long-term conservation and monitoring to support population resilience. Full article

The scattering interaction between a circularly polarized Bessel pincer light-sheet beam and a chiral particle is investigated within the framework of generalized Lorenz–Mie theory (GLMT). The incident electric field distribution is rigorously derived via the vector angular spectrum decomposition method (VASDM), with subsequent determination of the beam-shape coefficients (BSCs) $p_{mn}^u$ and $q_{mn}^u$ through multipole expansion in the basis of vector spherical wave functions (VSWFs). The expansion coefficients for the scattered field ($A_{mn}^s$$B_{mn}^s$) and interior field ($A_{mn}$$B_{mn}$) are derived by imposing boundary conditions. Simulations highlight notable variations in the scattering field, near-surface field distribution, and far-field intensity, strongly influenced by the dimensionless size parameter $ka$, chirality $\kappa$, and beam parameters (beam order l and beam scaling parameter ${\alpha }_0$). These findings provide insights into the role of chirality in modulating scattering asymmetry and localization effects. The results are particularly relevant for applications in optical manipulation and super-resolution imaging in single-molecule microbiology. Full article

Synthetic aperture radar (SAR) image target recognition has important application values in security reconnaissance and disaster monitoring. However, due to speckle noise and target orientation sensitivity in SAR images, traditional spatial domain recognition methods face challenges in accuracy and robustness. To effectively address these challenges, we propose a dual-branch spatial-frequency domain fusion recognition method with cross-attention, achieving deep fusion of spatial and frequency domain features. In the spatial domain, we propose an enhanced multi-scale feature extraction module (EMFE), which adopts a multi-branch parallel structure to effectively enhance the network’s multi-scale feature representation capability. Combining frequency domain guided attention, the model focuses on key regional features in the spatial domain. In the frequency domain, we design a hybrid frequency domain transformation module (HFDT) that extracts real and imaginary features through Fourier transform to capture the global structure of the image. Meanwhile, we introduce a spatially guided frequency domain attention to enhance the discriminative capability of frequency domain features. Finally, we propose a cross-domain feature fusion (CDFF) module, which achieves bidirectional interaction and optimal fusion of spatial-frequency domain features through cross attention and adaptive feature fusion. Experimental results demonstrate that our method achieves significantly superior recognition accuracy compared to existing methods on the MSTAR dataset. Full article

Astrocyte activation and gender differences play critical roles in the prognosis following stroke. Recent studies have shown that optogenetic technology can promote brain repair after stroke by activating astrocytes in male rats. However, it remains unclear whether gender differences influence the efficacy of optogenetic activation of astrocytes in regulating post-stroke brain repair and its underlying mechanisms. In this study, we activated astrocytes in the ipsilateral cortex of adult glial fibrillary acidic protein-channelrhodopsin 2-enhanced yellow fluorescent protein (GFAP-ChR2-EYFP) transgenic Sprague Dawley rats using optogenetic stimulation at 24, 36, 48, and 60 h after inducing photothrombosis stroke. Neurobehavioral tests, cresyl violet staining, RT-qPCR, Western blot, and immunofluorescence analysis were performed on both female and male rats. Our results showed that male rats exhibited significant improvements in behavioral scores and reduction in infarct size after optogenetic activation of astrocytes at three days post-stroke (p < 0.05), whereas no significant changes were observed in female rats. Additionally, in female rats, the expression of basic fibroblast growth factor (bFGF) increased after ischemic stroke and astrocytic optogenetic stimulation (p < 0.05), leading to enhanced endothelial cell proliferation compared to male rats (p < 0.05). In vitro experiments further demonstrated that the astrocyte activation was inhibited in the presence of bFGF (p < 0.05). These findings suggest that the increase in bFGF levels in females following stroke may inhibit the optogenetic activation of astrocytes, thereby attenuating the therapeutic effect of astrocyte activation on post-stroke brain repair. This study provides important insights into the gender-specific roles of astrocytes in the acute phase of ischemic stroke. Full article

Bacterial infections, particularly those caused by multidrug-resistant strains, remain a significant global public health challenge. The growing resistance to traditional antibiotics highlights the urgent need for novel antibacterial strategies. Herein, we successfully synthesized three types of nitrogen-doped carbon dots (tBuCz-CDs, HAH-CDs, and EC-CDs) via hydrothermal method using tert-butyl carbazate, hydroxyacetic acid hydrazide, and ethyl carbazate as precursors. tBuCz-CDs, HAH-CDs, and EC-CDs exhibited potent antibacterial activity against methicillin-resistant Staphylococcus aureus (MRSA), with minimum inhibitory concentrations (MICs) of 100, 100, and 150 µg/mL, respectively. Their antibacterial effect on MRSA was comparable to that of the widely used antibiotic vancomycin hydrochloride, as shown by the zone of inhibition assay. Furthermore, the carbon dots exhibited low cytotoxicity and hemolytic activity showing their excellent biocompatibility both in vitro and in vivo. They also significantly promoted wound healing compared to untreated controls. Notably, the serial passaging of MRSA exposed to these carbon dots did not result in the bacterial resistance. Mechanistic studies revealed that the carbon dots exerted antibacterial effects through multiple mechanisms, including the disruption of bacterial membranes, inhibition and eradication of biofilm formation, generation of reactive oxygen species, and DNA damage. This work highlights the potential of nitrogen-doped CDs as a promising material for combating drug-resistant bacterial infections and underscores their potential for further biomedical development. Full article

Longer inflorescence stalks in oil palm enhance harvesting efficiency and reduce labor costs. However, the research on this topic is limited. This study aimed to investigate the differences in stalk lengths between male and female inflorescences in Tenera oil palm and to elucidate the underlying hormonal and transcriptomic mechanisms. The stalk lengths from inflorescences associated with the fourth to eighteenth leaf positions of Tenera oil palm trees were measured, and hormone profiling and RNA sequencing (RNA-seq) were conducted in immature (F4 and M5) and mature (F14 and M13) stalks from an individual tree. The male stalks were significantly longer than the female stalks since the thirteenth inflorescences and the differences increased with maturation. The elevated levels of indole-3-acetic acid (IAA) in both immature and mature male stalks suggested auxin’s critical role in promoting stalk elongation. In M13, we identified the upregulated auxin influx carrier LAX2, Gibberellic Acid-Stimulated Arabidopsis 6 (GASA6), and SMALL AUXIN UP RNA (SAUR) genes, indicating enhanced auxin accumulation, signaling, and response. Moreover, the auxin response factor (ARF11) was upregulated, linking auxin transport to gene activation for cell elongation. Conversely, in F14, higher levels of abscisic acid (ABA) and the expression of ABA receptor PYL3 and gibberellin 2-beta-dioxygenase 8 GA2ox8, which may inhibit stalk elongation, were identified. The results suggested that LAX2-mediated IAA accumulation activates ARF11 and SAURs, promoting stalk elongation, with GASA6 possibly acting as a downstream modulator. This study provides insights into the hormonal and genetic regulators of stalk elongation in oil palm and may guide breeding strategies for oil palm varieties with longer stalks of female inflorescences, thereby enhancing harvesting efficiency. Full article

Alkyl sulfobetaine shows a strong advantage in the compounding of surfactants due to the defects in the size matching of hydrophilic and hydrophobic groups. The interfacial tensions (IFTs) of alkyl sulfobetaine (ASB) and xylene-substituted alkyl sulfobetaine (XSB) with oil-soluble (Span80) and water-soluble (Tween80) nonionic surfactants on a series of n-alkanes were studied using a spinning drop tensiometer to investigate the mechanism of IFT between nonionic and betaine surfactants. The two betaine surfactants’ IFTs are considerably impacted differently by Span80 and Tween80. The results demonstrate that Span80, through mixed adsorption with ASB and XSB, can create a relatively compacted interfacial film at the n-alkanes–water interface. The equilibrium IFT can be reduced to ultra-low values of 5.7 × 10⁻³ mN/m at ideal concentrations by tuning the fit between the size of the nonionic surfactant and the size of the oil-side vacancies of the betaine surfactant. Nevertheless, Tween80 has minimal effect on the IFT of betaine surfactants, and the betaine surfactant has no vacancies on the aqueous side. The present study provides significant research implications for screening betaine surfactants and their potential application in enhanced oil recovery (EOR) processes. Full article

When ships conduct offshore operations in the ocean, they are subject to disturbances from natural factors such as sea breezes and waves. These disturbances lead to movements detrimental to the ship’s stability, especially heave movement in the vertical direction, which profoundly impacts the safety of shipboard facilities and staff. To counter this, the active wave compensation device is widely used on ships to maintain the stability of the working environment. However, the system’s efficiency and accuracy are compromised by the significant delay incurred while obtaining real-time motion signals and driving the actuator for motion compensation. To solve the time delay problem of shipborne wave compensation equipment in motion compensation under complex sea conditions, it is necessary to improve the ship heave motion prediction accuracy in an active wave compensation system. This paper presents a prediction method of ship heave motion based on the particle swarm optimization (PSO) and convolutional neural network–long short-term memory (CNN-LSTM) hybrid prediction model. The paper begins by establishing the ship heave motion model based on the P–M spectrum and slice theory, simulating the ship heave motion curve under different sea conditions on MATLAB. This simulation provides crucial data for the subsequent prediction model. The paper then delves into the realization method of ship heave motion based on PSO-CNN-LSTM, where the convolutional neural network (CNN) is used to extract the features of the input signal, thereby enhancing the multi-source feature fusion ability of the LSTM neural network model. The PSO algorithm is then employed to optimize the network structure and hyperparameters of the convolutional neural network. The experiments demonstrate that the proposed PSO-CNN-LSTM hybrid model effectively addresses the problem of predicting drift and boasts significantly higher prediction accuracy, making it suitable for predicting the short-term heave motion of ships. The data show that the optimized root mean square error (RMSE) value under level 5 sea conditions is 0.01265 compared to 0.01673 before optimization, and the optimized RMSE value under level 6 sea conditions is 0.01140 compared to 0.01479 before optimization, which demonstrates that the error between the predicted value and the actual value of the model decreases. This improved accuracy provides reassurance in the model’s predictive capabilities and lays the foundation for improving the accuracy of the motion compensation system in the future. Full article

The Cuyu gold deposit in central Jilin Province in Northeast China is located in the eastern segment of the northern margin of the North China Craton (NCC), as well as the eastern segment of the Xing’an–Mongolian Orogenic Belt (XMOB). Gold ore-bodies are controlled by NW-trending faults and mainly occur in late Hercynian granodiorite. The mineralization process in the Cuyu deposit can be divided into three stages: quartz + coarse grained arsenopyrite + pyrite (stage I), quartz + sericite + pyrite + arsenopyrite + electrum + chalcopyrite + sphalerite (stage II), and quartz + calcite ± pyrite (stage III). Stage II is the most important for gold mineralization. We conducted analyses including petrography, microthermometry, laser Raman spectroscopy of fluid inclusions, and H–O–S–Pb isotopic analysis to elucidate the mineralization processes in the Cuyu deposit. Five types of primary fluid inclusions (FIs) are present in the hydrothermal quartz and calcite grains of the ore: liquid-rich two-phase aqueous fluid inclusions (L-type), vapor-rich two-phase aqueous fluid inclusions (V-type), CO₂-bearing two- or three-phase inclusions (C1-type), CO₂-rich two- or three-phase inclusions (C2-type), and pure CO₂ mono-phase inclusions (C3-type). From stages I to III, the fluid inclusion assemblages changed from L-, C2-, and C3-types to L-, V-, C1-, C2-, and C3-types and, finally, to L-types only. The corresponding homogenization temperatures for stages I to III were 242–326 °C, 202–298 °C, and 106–188 °C, and the salinities were 4.69–9.73, 1.63–7.30, and 1.39–3.53 wt.% NaCl equiv., respectively. The ore-forming fluid system evolved from a NaCl-H₂O-CO₂ ± CH₄ ± H₂S fluid system in stage I and II with immiscible characteristics to a homogeneous NaC-H₂O fluid system in stage III. Microthermometric data for stages I to III show a decreasing trend in homogenization temperatures and salinities. The mineral assemblages, fluid inclusions, and H–O–S–Pb isotopes indicate that the initial ore-forming fluids of stage I were exsolved from diorite porphyrite and characterized by a high temperature and low salinity. The addition of meteoric water in large quantities led to decreases in temperature and pressure, resulting in a NaCl-H₂O-CO₂ ± CH₄ ± H₂S fluid system with significant immiscibility in stage II, facilitating the deposition of gold and associated polymetallic sulfides. The Cuyu gold deposit has a similar ore genesis to those of gold deposits in the Jiapigou–Haigou gold belt (JHGB) of southeastern Jilin Province indicating potential for gold prospecting in the northwest-trending seam of the JHGB. Full article

The complex burst characteristic parameters of SCB were subjected to dimensionality reduction using principal component analysis (PCA), enabling accurate evaluation of the output performance of SCB. The accuracy and reliability of the PCA method were also validated. A 100 μF tantalum capacitor was utilized to excite the SCB, while a digital oscilloscope recorded the characteristic parameters of the SCB explosion. The experimental results demonstrate that the critical burst time of SCB decreases with the rising voltage, and the critical burst energy decreases first and then increases with the rising voltage. The total burst time and total burst energy of SCB all decrease first and then increase with the rise of voltage. The PCA results indicate that as the voltage increases, the score of SCB output capacity initially decreases and then increases, reaching its lowest point at 17 V. The SCB was utilized to ignite lead styphnate (LTNR) under varying circuit conditions; the characteristic parameters obtained were analyzed using PCA to derive comprehensive scores. The same dataset was then input into the PCA model for pure SCB to calculate corresponding comprehensive scores. The consistency between the two sets of scores validated the accuracy and reliability of PCA in assessing SCB output capability. Full article

Quantifying extreme weather events (EWEs) and understanding their impacts on vegetation phenology is crucial for assessing ecosystem stability under climate change. This study systematically investigated the ecosystem growing season length (GL) response to four types of EWEs—extreme heat, extreme cold, extreme wetness (surplus precipitation), and extreme drought (lack of precipitation). The EWE extremity thresholds were found statistically using detrended long time series (2000–2022) ERA5 meteorological data through z-score transformation. The analysis was based on a grassland ecosystem in the Mongolian Plateau (MP) from 2000 to 2022. Using solar-induced chlorophyll fluorescence data and event coincidence analysis, we evaluated the probability of GL anomalies coinciding with EWEs and assessed the vegetation sensitivity to climate variability. The analysis showed that 83.7% of negative and 87.4% of positive GL anomalies were associated with one or more EWEs, with extreme wetness (27.0%) and extreme heat (25.4%) contributing the most. These findings highlight the dominant role of EWEs in shaping phenological shifts. Negative GL anomalies were more strongly linked to EWEs, particularly in arid and cold regions where extreme drought and cold shortened the growing season. Conversely, extreme heat and wetness had a greater influence in warmer and wetter areas, driving both the lengthening and shortening of GL. Furthermore, background hydrothermal conditions modulated the vegetation sensitivity, with warmer regions being more susceptible to heat stress and drier regions more vulnerable to drought. These findings emphasize the importance of regional weather variability and climate characteristics in shaping vegetation phenology and provide new insights into how weather extremes impact ecosystem stability in semi-arid and arid regions. Future research should explore extreme weather events and the role of human activities to enhance predictions of vegetation–climate interactions in grassland ecosystems of the MP. Full article

Arabinogalactan proteins (AGPs) constitute a diverse class of hydroxyproline-rich glycoproteins implicated in various aspects of plant growth and development. However, their functional characterization in cotton (Gossypium spp.) remains limited. As a globally significant economic crop, cotton serves as the primary source of natural fiber, making it essential to understand the genetic mechanisms underlying its growth and development. This study aims to perform a comprehensive genome-wide identification and characterization of the AGP gene family in Gossypium spp., with a particular focus on elucidating their structural features, evolutionary relationships, and functional roles. A genome-wide analysis was conducted to identify AGP genes in Gossypium spp., followed by classification into distinct subfamilies based on sequence characteristics. Protein motif composition, gene structure, and phylogenetic relationships were examined to infer potential functional diversification. Subcellular localization of a key candidate gene, GhAGP50, was determined using fluorescent protein tagging, while gene expression patterns were assessed through β-glucuronidase (GUS) reporter assays. Additionally, hormonal regulation of GhAGP50 was investigated via treatments with methyl jasmonate (MeJA), abscisic acid (ABA), indole-3-acetic acid (IAA), and gibberellin (GA). A total of 220 AGP genes were identified in Gossypium spp., comprising 19 classical AGPs, 28 lysine-rich AGPs, 55 AG peptides, and 118 fasciclin-like AGPs (FLAs). Structural and functional analyses revealed significant variation in gene organization and conserved motifs across subfamilies. Functional characterization of GhAGP50, an ortholog of AGP18 in Arabidopsis thaliana, demonstrated its role in promoting epidermal hair formation in leaves and stalks. Subcellular localization studies indicated that GhAGP50 is targeted to the nucleus and plasma membrane. GUS staining assays revealed broad expression across multiple tissues, including leaves, inflorescences, roots, and stems. Furthermore, hormonal treatment experiments showed that GhAGP50 expression is modulated by MeJA, ABA, IAA, and GA, suggesting its involvement in hormone-mediated developmental processes. This study presents a comprehensive genome-wide analysis of the AGP gene family in cotton, providing new insights into their structural diversity and functional significance. The identification and characterization of GhAGP50 highlight its potential role in epidermal hair formation and hormonal regulation, contributing to a deeper understanding of AGP functions in cotton development. These findings offer a valuable genetic resource for future research aimed at improving cotton growth and fiber quality through targeted genetic manipulation. Full article

Extracting nodal features is crucial for analyzing rock structure stability and plays a significant role in designing engineering projects. This study presents an enhanced version of the FraSegNet algorithm, focusing on improving its ability to identify nodal features in images. The updated FraSegNet incorporates the ResNet101 backbone and integrates the Squeeze-and-Excitation (SE) attention mechanism, enabling better concentration on key nodal characteristics. The primary improvements are as follows: (1) Multi-scale feature extraction: Leveraging the ResNet101 architecture for the effective extraction of detailed information from nodal images. (2) Better attention mechanisms: The SE module focuses on nodal regions, resulting in clearer and more refined feature representations. (3) Dynamic learning strategies: I incorporation of cosine annealing and warm-up techniques to optimize training efficiency. The algorithm was validated with the Barton–Bandis model and Hoek–Brown criterion. The experimental results demonstrate its superior performance, achieving 97.1% accuracy in nodal feature detection with an average error of only 1.5% compared to the rock mass parameter. This small error proves the model works well. FraSegNet offers accurate segmentation and precise geometric parameter extraction, making it a valuable tool for advancing rock stability analysis and practical applications in rock mechanics. Full article

PAH contamination from coking plants have received widespread attention. However, the microbial diversity, co-occurrence patterns, and functional genes of bacteria in aged coking contaminated soils by PAHs are still not clear. In our study, we used a macro-genetic approach to detect PAH-contaminated soils from both a coking production area (CA group) and an office zone (OA group) in an abandoned coking plant, and analyzed the characteristic bacteria and function genes, microbial network interaction patterns, and soil P-cycling in long-term PAH-contaminated soils. The results revealed that Proteobacteria were significantly positively correlated with PAHs and Betaprobacteria bacterium rifcsplowo2 12 full 6514, candidatus Muproteobacteria bacterium RBG16609, and Sulfurifustis variabilis, which belong to Proteobacteria, were characteristic bacteria in PAH-contaminated soils. The phn, which is the PAH degradation gene, was abundantly expressed in the PAH-contaminated soil. The phn gene cluster genes (phnE, phnC, and phnD) were significantly expressed in the CA group of PAH-contaminated soils (p < 0.05). By integrating microbial diversity, network structure, and functional genes, it offers a comprehensive understanding of soil ecosystem response indicators to prolonged PAH stress. The results of this study will provide new ideas for constructing an assessment index system for soil health and screening biomarkers for PAH-contaminated soils. Full article

Proton exchange membrane fuel cells (PEMFCs), recognized as promising sources of waste heat for space heating, domestic hot water supply, and industrial thermal applications, have garnered substantial interest owing to their environmentally benign operation and high energy conversion efficiency. Since the uniformity of oxygen diffusion toward catalytic layers critically governs electrochemical performance, this study establishes a three-dimensional, non-isothermal computational fluid dynamics (CFD) model to systematically optimize the cathode flow channel width distribution, targeting the maximization of power output through enhanced reactant homogeneity. Numerical results reveal that non-uniform flow channel geometries markedly improve oxygen distribution uniformity, reducing the flow inhomogeneity coefficient by 6.6% while elevating maximum power density and limiting current density by 9.1% and 7.8%, respectively, compared to conventional equal-width designs. There were improvements attributed to the establishment of longitudinal oxygen concentration gradients and we alleviated mass transfer limitations. Synergistic integration with gas diffusion layer (GDL) gradient porosity optimization further amplifies performance, yielding a 12.4% enhancement in maximum power density and a 10.4% increase in limiting current density. These findings validate the algorithm’s efficacy in resolving coupled transport constraints and underscore the necessity of multi-component optimization for advancing PEMFC design. Full article