Search Results (1,477)

Northwestern Jiangxi Province is rich in metasilicic acid (as H₂SiO₃) mineral water resources. Investigating their hydrogeochemical characteristics and formation mechanism is crucial for the rational utilization of water resources and the sustainable development of the local mineral water industry. Taking the Taoping water source area in northwestern Jiangxi as a case study, 11 sets of groundwater and surface water samples were systematically collected. By comprehensively applying mathematical statistics, ionic ratios, and isotopic analyses, the hydrogeochemical characteristics and formation processes of metasilicic acid-type mineral water were examined. The results indicate that: (1) The mineral waters in the area are weakly alkaline and belong to the metasilicic acid type, with concentrations ranging from 22.0 to 67.0 mg/L, of which 75% exceed 30 mg/L. (2) The primary hydrochemical types are HCO₃⁻–Ca·Na, HCO₃⁻–Ca·Mg, and HCO₃⁻–Ca. Analysis of stable isotopes (δ¹⁸O and δ²H) and tritium (³H) indicates that metasilicic acid mineral water is primarily recharged by atmospheric precipitation, with an apparent groundwater age of approximately 60 years. (3) The enrichment of metasilicic acid primarily results from the weathering and leaching of silicate minerals, coupled with cation exchange. K⁺ and Na⁺ are mainly derived from silicate minerals such as feldspars and halite, whereas Ca²⁺ and Mg²⁺ originate primarily from carbonate minerals like calcite and dolomite. During recharge, atmospheric precipitation infiltrates the aquifer, dissolving aluminosilicate and siliceous minerals in the surrounding rocks, thereby releasing metasilicic acid into the groundwater and ultimately forming the metasilicic acid-type mineral water. Full article

Aiming to predict the evolution of fracture structures under stress conditions and the Permeability process of the fracture network, a damage evolution model reflecting the coupling mechanism between topological characteristics and mechanical responses of fracture networks is established based on yield criteria and complex network theory, realizing a prediction for permeability processes. Firstly, key parameters such as degree centrality, betweenness centrality, and clustering coefficient of fracture nodes are extracted through complex network topological analysis. Combined with the finite element method to calculate the node shear stress transfer coefficient, a topology–mechanics coupling model of the fracture network is constructed. Secondly, the Coulomb–Mohr yield criterion is improved to establish a damage evolution equation considering normal stress and shear stiffness degradation. Based on the above theory, a fracture network permeability iterative algorithm was developed to simultaneously update the network topology and the stress distribution of the fracture network. The evolution process of the network was analyzed based on the adjacency matrix and the changes in the number of connected clusters. The results show that the average degree of the largest cluster directly reflects the connectivity of the fracture network; a higher average degree corresponds to greater damage to the fracture network under stress. The average clustering coefficient indicates the extent of local connectivity; a higher clustering coefficient signifies denser local connections, which enhances the fracture network connectivity. Compared with traditional static methods, the dynamic damage evolution model has a permeability prediction error within 7%, indicating the effectiveness of this method. Full article

The Body Mass Index (BMI), integrating body weight and length, is a widely used metric for obesity assessment in humans. As pigs serve as crucial biomedical models, the application of BMI in swine and its genetic basis remain poorly explored. This study aimed to investigate the genetic architecture of pig BMI and compare two carcass-based BMI metrics (BMI-S and BMI-O) for breeding applicability. A total of 439 Landrace × Yorkshire crossbred pigs were genotyped with a 50 K SNP chip; heritability was estimated via a mixed linear model, and genome-wide association study (GWAS) was performed using the BLINK model. BMI-S and BMI-O exhibited moderate-to-high heritability of 0.55 and 0.47, respectively, with 17 genome-wide significant SNPs detected—including the top associated SNP rs81382440 on chromosome 4 and rs80898583 on chromosome 7. Key candidate genes (GPHN, ADAM33, KCNH8, PDCD4) and 5 SNP-trait associations validated in PigQTLdb were linked to lipid/energy metabolism and muscle development. Carcass-based BMI improved phenotypic accuracy, and our findings provide core genetic markers and a theoretical basis for molecular breeding of pig body conformation and lipid deposition traits. Full article

As a natural flavonoid compound, quercetin possesses excellent antioxidant, anti-inflammatory and anti-atherosclerotic activities. However, the poor water solubility and sensitivity to the environment severely limit the application of quercetin. Initially, quercetin-loaded zein/carboxymethyl chitosan nanoparticles (ZCQ NPs) were prepared using an anti-solvent precipitation method. The fabricated ZCQ NPs exhibited a small particle size and polydispersity index (PDI). The ZCQ NPs had a negative zeta potential with an absolute value of 41.50 ± 1.76 mV. ZCQ NPs could remain highly stable against light, heat and ion strength. In addition, ZCQ NPs maintained good monodispersity and displayed minimal changes in particle size under long-term storage conditions. Additionally, a superior antioxidant capacity of ZCQ NPs was also observed in the free radical and reactive oxygen species (ROS) scavenging study compared to that of free quercetin. All these results of this study suggest that ZCQ NPs could serve as an effective drug delivery system for encapsulating and delivering quercetin. Full article

Wild ginkgo, as an endangered species, holds significant value for genetic resource conservation, yet its practical applications face numerous challenges. Traditional field surveys are inefficient in mountainous mixed forests, while satellite remote sensing is limited by spatial resolution. Current deep learning approaches relying on single-source data or merely simple multi-source fusion fail to fully exploit information, leading to suboptimal recognition performance. This study presents a multimodal ginkgo crown dataset, comprising RGB and multispectral images acquired by an UAV platform. To achieve precise crown segmentation with this data, we propose a novel dual-branch dynamic weighting fusion network, termed dual-branch cross-modal attention-enhanced UNet (DCA-UNet). We design a dual-branch encoder (DBE) with a two-stream architecture for independent feature extraction from each modality. We further develop a cross-modal interaction fusion module (CIF), employing cross-modal attention and learnable dynamic weights to boost multi-source information fusion. Additionally, we introduce an attention-enhanced decoder (AED) that combines progressive upsampling with a hybrid channel-spatial attention mechanism, thereby effectively utilizing multi-scale features and enhancing boundary semantic consistency. Evaluation on the ginkgo dataset demonstrates that DCA-UNet achieves a segmentation performance of 93.42% IoU (Intersection over Union), 96.82% PA (Pixel Accuracy), 96.38% Precision, and 96.60% F1-score. These results outperform differential feature attention fusion network (DFAFNet) by 12.19%, 6.37%, 4.62%, and 6.95%, respectively, and surpasses the single-modality baselines (RGB or multispectral) in all metrics. Superior performance on cross-flight-altitude data further validates the model’s strong generalization capability and robustness in complex scenarios. These results demonstrate the superiority of DCA-UNet in UAV-based multimodal ginkgo crown recognition, offering a reliable and efficient solution for monitoring wild endangered tree species. Full article

Cutaneous T-cell lymphoma (CTCL) is a heterogeneous malignancy characterized by the proliferation of skin-homing CD4⁺ T cells and profound immune dysregulation within the tumor microenvironment (TME). This review synthesizes evidence on chemokine–receptor networks that govern malignant T-cell trafficking among blood, skin, and lymph nodes, the formation of immunosuppressive niches, and clinically actionable biomarker candidates. Among the best-supported axes, CCL17/CCL22–CCR4 and CCL27/CCL28–CCR10 mediate skin tropism, CCL19/CCL21–CCR7 contributes to lymph node homing, and CXCL12–CXCR4 supports skin trafficking and is associated with disease progression. In contrast, CCR2/CCR5/CCR6/CCR8-centered circuits and CXCR3/CXCR5 pathways are emerging regulators of myeloid recruitment, regulatory T-cell accumulation, and context-dependent immune activation. Therapeutically, agents targeting chemokine pathways, most notably the CCR4 monoclonal antibody Mogamulizumab, have demonstrated clinical efficacy, while emerging inhibitors of CCR6, CCR5, and CXCR4 offer promising avenues for intervention. We further highlight how recent single-cell and other high-dimensional omics studies refine cell-type–specific chemokine sources and receptor expression, enabling more precise mapping of chemokine-driven intercellular communication programs in CTCL TME remodeling and better prioritization of therapeutic targets and biomarkers. Full article

Ovarian cancer (OC), the third most common gynecologic malignancy, is characterized by high mortality largely driven by chemotherapy resistance, leading to recurrence and metastasis. Using transcriptomic data from GSE73935, we constructed a weighted gene co-expression network and identified eight hub genes (IGF1R, CDH2, PDGFRA, CDKN1A, SHC1, SPP1, CAV1 and FGF18) associated with cisplatin resistance, among which CDH2 emerged as the most clinically relevant candidate. CDH2 demonstrated moderate diagnostic potential (AUC = 0.792) and was markedly upregulated in cisplatin-resistant A2780/CP70 cells. Independent validation using clinical single-cell RNA-seq data (GSE211956) confirmed its selective enrichment in resistant tumor cell subpopulations. Gene set enrichment analysis linked elevated CDH2 expression to p53 signaling, DNA replication, nucleotide excision repair, and Toll-like receptor pathways, with qPCR supporting upregulation of key downstream genes in resistant cells. Immune deconvolution further indicated that high CDH2 expression correlated with increased infiltration of NK cells, Tregs, macrophages, and neutrophils, and immunohistochemistry verified CDH2 overexpression in cisplatin-resistant tissues. In addition, virtual screening and drug sensitivity profiling identified several FDA-approved agents with potential relevance to CDH2-associated drug response. These findings indicate that CDH2 may serve as a candidate marker associated with cisplatin response in OC, and its association with immune cell infiltration provides further insight into mechanisms potentially underlying chemoresistance. Full article

In recent years, biomass utilization has attracted extensive attention. Herein, hexagonal/cubic ZnIn₂S₄ (ZIS) heterojunction catalysts were synthesized via a solvothermal method for the selective oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-diformylfuran (DFF). The results demonstrated that the constructed heterojunctions effectively promoted carrier separation. The optimal catalyst achieved an HMF conversion rate of 88.8% and a DFF yield of 86.6% within 1 h in the open air. X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) characterizations confirmed the successful fabrication of the composite phase structure and revealed a porous spherical morphology. Equivalent circuit fitting of electrochemical impedance spectroscopy (EIS) data indicated that the hexagonal/cubic heterojunctions possessed the lowest charge transfer resistance (Rct = 5825 Ω), which effectively reduced interfacial charge transfer resistance and accelerated the transport of photoinduced carriers. Radical quenching experiments and electron paramagnetic resonance (EPR) spectroscopy identified superoxide radicals (·O₂⁻) as the primary reactive species. Meanwhile, density functional theory (DFT) calculations elucidated the formation of the built-in electric field and the charge transfer mechanism. This work’s construction of Type-II ZIS heterojunctions effectively addressed the issue of rapid carrier recombination in pristine ZIS materials, providing a feasible strategy for biomass valorization. Full article

Citrus trees are mainly cultivated in acidic soils. Excessive manganese (Mn) is the second most limiting factor for crop productivity in acidic soils after aluminum toxicity. The roles of reactive oxygen species (ROS) and methylglyoxal (MG) detoxification systems in augmented pH-mediated amelioration of excessive Mn are poorly understood. ‘Sour pummelo’ (Citrus grandis (L.) Osbeck) seedlings were exposed to nutrient solution at a Mn concentration of 500 (Mn500) or 2 (Mn2) μM and a pH of 3 (P3) or 5 (P5). The increase in pH attenuated Mn500-induced increases in ROS production and MG and malondialdehyde accumulation in roots and leaves. Additionally, the increase in pH enhanced the coordinated detoxification capability of both ROS and methylglyoxal scavenging systems in these tissues under Mn500. These findings corroborated the hypothesis that augmenting pH enhances the capability of these tissues to detoxify ROS and methylglyoxal under Mn excess. Therefore, this study provided new evidence on the roles of ROS and MG detoxification systems in the augmented pH-mediated amelioration of oxidative damage in ‘Sour pummelo’ leaves and roots caused by Mn excess, as well as a basis for correcting Mn toxicity by augmenting soil pH. Full article

Air-cooled steel is a high-strength steel widely used in automotive subframe applications. In this study, the microstructural evolution and fatigue performance of air-cooled steel welded joints subjected to a one-step heat treatment and an additional two-step heat treatment were systematically investigated. The results indicate that, after the one-step heat treatment, the microstructure of the welded joints transformed from coarse lath martensite to a mixture of tempered martensite and newly formed martensite. After the two-step heat treatment, the microstructure of the welded joints evolved from coarse lath martensite to newly formed martensite, M-A islands, bainitic ferrite, and a small amount of polygonal ferrite. Under both heat treatment conditions, the fatigue limits of the welded specimens were lower than those of the base metal, which can be attributed to the reduced overall deformation compatibility induced by the welded joints. In addition, the welded joints exhibited superior crack propagation resistance compared with the base metal after both heat treatment processes, which is likely related to the enhanced ability of dislocation structures and grain boundaries to impede crack propagation. Full article

Academic conferences have been pivotal in scholarly communications, facilitating the exchange of ideas and fostering collaborations among attendees by using advanced sensing, networking, and control technologies. Traditionally held in physical venues, the landscape of academic conferences has been revolutionised by the advent of virtual and hybrid formats as supported by the Internet of Things, Artificial Intelligence, and virtual reality tools. Despite the burgeoning literature on smart conferences, there exists a gap in comprehensive reviews that consolidate the various advancements and methodologies in this domain. This article aims to fill this gap by providing a thorough review of the latest developments in smart conference technologies and practices. It offers a multidimensional analysis, including predictive analytics, smart content delivery, networking improvements, and data-driven assessments. Fundamentally, we frame conference activities as a complex process involving multi-stage planning, real-time dynamic execution, and post-event analysis and refinement. This review specifically highlights how smart technologies are transforming this end-to-end process. Additionally, the concept of parallel intelligence is introduced, exploring its potential to transform future conferences. The significance of this article lies in its holistic perspective, offering valuable insights for enhancing conference planning, attendee engagement, and overall conference experiences. Full article

Background/Objectives: The objective of this study is to evaluate the association between retinal ischemic perivascular lesions (RIPLs) and cardiovascular diseases (CVDs) among patients diagnosed with severe carotid artery stenosis (SCAS). Methods: Consecutive patients (123 patients) with SCAS were included and underwent swept-source optical coherence tomography angiography (SS-OCTA). Retinal structural and blood flow parameters of the macular region were calculated and compared between patients with and without CVD. The prevalence of RIPLs confirmed on B-scan images was compared between patients with and without CVD. The relationship between RIPLs and CVD in patients with SCAS was explored using multivariate logistic regression analysis. Subgroup analysis was conducted to evaluate the relationship between ipsilateral RIPLs, contralateral RIPLs, and bilateral RIPLs and CVD. Results: Of the 123 patients with SCAS, 61 patients (49.6%) had a history of CVD. The CVD group had lower vessel density in the superficial and deep retinal vascular complexes, thinner inner retinal thickness, and thicker outer retinal thickness compared with the non-CVD group. A higher prevalence of RIPLs was found in the CVD group compared to the non-CVD group (55.7% vs. 30.6%, p = 0.006). The presence of RIPLs was significantly associated with CVD in SCAS patients (OR = 3.953 [1.695–9.219], p = 0.001) after adjusting for covariates. Subgroup analysis revealed greatest risk of bilateral RIPLs for CVD (OR = 7.383 [1.749–30.393], p = 0.006), followed by contralateral RIPLs (OR = 4.024 [1.432–11.306], p = 0.008) and ipsilateral RIPLs (OR = 2.951 [1.258–6.921], p = 0.013). Conclusions: The presence of RIPLs is significantly associated with CVD in SCAS patients. Findings of this research demonstrated that evaluation of RIPLs may help identify high-risk SCAS patients and facilitate special medical care for this group of patients. Full article

Silicon is commonly used in micro/nano-electromechanical system (MEMS/NEMS) devices. Because detailed information about the friction interface in these systems is lacking, the relationship between texture shape and friction remains unclear. In this study, molecular dynamics simulations were performed to investigate the dry-friction tribological behavior of crystalline silicon, focusing on the effects of surface roughness, normal load, and sliding speed. The results show that between normal loads of 4 GPa and 8 GPa, the average frictional force exhibits significant nonlinear behavior under a sliding speed of 0.2 Å/ps. The approximate steady value of the friction coefficient is 0.39, which is in good agreement with the experimental result of 0.37. Under a normal load of 5 GPa, the friction force increases linearly from 110 nN at 0.05 Å/ps to 311 nN at 2 Å/ps. In addition, in systems with sinusoidal surface roughness, the amplitude has a greater effect on the frictional properties than the period. Among the four rough surfaces studied, A10T32 exhibits the lowest friction force and friction coefficient. This provides theoretical support for the further design of MEMS/NEMS devices with long operational lifetimes. Full article

The Lorentz invariance violation (LIV) predicted by some quantum gravity theories would manifest as an energy-dependent speed of light, which may potentially distort the observed temporal profile of photons from astrophysical sources at cosmological distances. The dispersion cancellation (DisCan) algorithm offers a powerful methodology for investigating such effects by employing quantities such as Shannon entropy, which reflects the initial temporal characteristics. In this study, we apply the DisCan algorithm to search for LIV effects in the LHAASO observations of GRB 221009A, combining data from both the Water Cherenkov Detector Array (WCDA) and Kilometer Squared Array (KM2A) detectors that collectively span an energy range of ∼0.2–13 TeV. Our analysis accounts for the uncertainties from both energy resolution and temporal binning. We derive $95\%$ confidence level lower limits on the LIV energy scale of $E_{\mathrm{QG},1}/{10}^{19}\mathrm{GeV}>14.6$ (11.2) for the first-order subluminal (superluminal) scenario, and $E_{\mathrm{QG},2}/{10}^{11}\mathrm{GeV}>13.7$ (12.5) for the second-order subluminal (superluminal) scenario. Full article

In the context of a high proportion of renewable energy integration, active splitting section search—one of the “three defense lines” of a power system—is crucial for the security, stability, and long-term sustainability of islanded grids. Addressing the random fluctuations of high-penetration wind power and the weakened voltage support capability caused by multi-infeed HVDC, this paper proposes a slow-coherency-based active splitting section optimization model that explicitly accounts for wind power uncertainty and multi-infeed DC stability constraints. First, a GMM-K-means method is applied to historical wind data to model, sample, and cluster scenarios, efficiently generating and reducing a representative set of typical wind outputs; this accurately captures wind uncertainty while lowering computational burden. Subsequently, an improved particle swarm optimizer enhanced by genetic operators is used to optimize a multi-dimensional coherency fitness function that incorporates a refined equivalent power index, frequency constraints, and connectivity requirements. Simulations on a modified New England 39-bus system demonstrate that the proposed model markedly enlarges the post-split voltage stability margin and effectively reduces power-flow shocks and power imbalance compared with existing methods. This research contributes to enhancing the sustainability and operational resilience of power systems under energy transition. Full article