Search Results (2,795)

Traditional leaf area index (LAI) measurement methods are destructive, time-consuming, and labor-intensive. In this study, 282 four-year-old central-leader apple trees were used as research subjects. Canopy reflectance spectra in the range of 4000−10,000 cm⁻¹ were collected, and the corresponding true LAI values were measured destructively by harvesting all leaves from a representative branch of each tree using a leaf area meter. The dataset was randomly divided into training (70%) and testing (30%) sets. Eight spectral pretreatment methods were compared. The Competitive Adaptive Reweighted Sampling (CARS) algorithm was employed to extract characteristic wavelengths. Subsequently, both a BP neural network and a Support Vector Machine (SVM) model for LAI prediction were constructed. The optimal model was selected based on evaluation metrics including the coefficient of determination (R²), mean absolute error (MAE), mean bias error (MBE), and mean absolute percentage error (MAPE). The combined preprocessing of MSC and SD yielded the optimal results, screening out 26 characteristic wavelengths. The SVM linear kernel model (c = 5, g = 0.3) constructed based on MSC + SD preprocessing performed best, achieving a validation set R² of 0.90, MAE of 0.2117, MBE of −0.1214, and MAPE of 16.09%. The performance on the training set and validation set was comparable, with no overfitting observed. The MSC + SD preprocessing combined with CARS feature screening and SVM linear kernel modeling enables rapid, non-destructive estimation of apple canopy LAI, providing an effective technical tool for precision orchard management. Full article

The rapid integration of distributed solar photovoltaic (PV) generation is reshaping low-voltage distribution grids (LVDGs), creating voltage rise, reverse power flow, and congestion challenges for distribution system operators (DSOs). Flexibility in generation and demand, broadly understood as the capability to adjust generation or consumption in response to variability and uncertainty in net load, is increasingly central to cost-effective grid operation under high PV penetration. This review examines flexibility and controllability options in LVDGs, focusing on voltage regulation methods, supply- and demand-side flexibility resources, and market-based coordination mechanisms. The Norwegian Regulation on Quality of Supply (FoL) provides the regulatory context: it enforces 1 min average voltage compliance, stricter than the 10 min averaging window of EN 50160, making short-duration voltage excursions operationally significant and directly influencing the trade-off between curtailment, grid reinforcement, and local flexibility measures. Inverter-based active–reactive power control emerges as the most cost-effective overvoltage mitigation option, complemented by local battery energy storage systems (BESS) and demand response for congestion relief and energy shifting. Key gaps include limited LV observability, insufficient application of quasi-static time series (QSTS) assessment in planning, and underdeveloped DSO-aggregator coordination frameworks. Combined inverter control, feeder-end storage, and demand-side flexibility can defer costly reinforcements, particularly in rural 230 V IT feeders where voltage constraints dominate. Full article

Intranasal administration is a promising drug delivery route enabling precise and rapid central nervous system targeting. In our previous work, twelve hybrid colloidal dispersions were developed, consisting of synthetic poly(ethylene-oxide)-b-poly(ε-caprolactone) (PEO-b-PCL) block copolymers with an increasing proportion of the hydrophobic PCL segment, Tween 80 (Tw80) and β-cyclodextrin derivatives (βCD), either methyl-β-CD (MβCD) or hydroxy-propyl-β-CD (HPβCD) for IN delivery of ropinirole hydrochloride (RH). Colloidal dispersions were prepared at different weight ratios (system/RH equal to 10:1 and 10:5), characterized and evaluated in vitro. The aim of this study is to evaluate the ex vivo permeation through rabbit nasal mucosa and determine the pharmacokinetic parameters of RH, when administered intranasally as a colloidal dispersion, compared with oral and intranasal RH solutions in C57BL/6J mice. Ex vivo permeation studies showed that all formulations significantly enhanced RH permeation compared to the pure RH solution (0.5 mg/mL, pH 5.6). Among them, F4 [(PEO-b-PCL₁/Tw80/HPβCD)/RH 10:5] was selected for further investigation. Pharmacokinetic analysis showed that F4 significantly enhanced both systemic and brain exposure of RH, achieving higher serum AUC and C_max values, despite a 3-fold lower administered dose compared to the oral dose. It showed high systemic (F_rel(Serum) = 1815%) and brain (F_rel(Brain) = 363%) relative bioavailability compared with oral administration, underscoring its potential as an intranasal delivery system for efficient CNS targeting. Full article

Building upon our previous research in which we derived two formulations of the governing equations expressed in terms of $\left(\rho ,\mathit{B},\mathit{v}\right)$ and the perturbation displacement $\mathit{\xi }$, we extend our analysis to investigate the dispersion relation of linear magnetohydrodynamic (MHD) waves in a one-dimensional flux-sheet magneto-lattice. The convergence of the dispersion relations is examined by increasing the truncation order of the reciprocal lattice vectors from 3 to 10, for the central equations expressed in terms of $\left(\rho ,\mathit{B},\mathit{v}\right)$, and for modulation amplitudes of $B_m=0.01$, $0.02$, $0.1$, $0.2$, $0.3$ and $0.4$. The dispersion relations obtained at different truncation orders exhibit rapid convergence for small modulation amplitudes $B_m$, with only minor discrepancies emerging as $B_m$ increases, indicating overall satisfactory convergence of the plane wave expansion (PWE) method within the investigated parameter range. A comparative analysis with the previously studied sinusoidal magneto-lattice reveals that, while the overall dispersion structure remains qualitatively similar, the flux-sheet magneto-lattice yields wider bandgaps at equivalent modulation amplitudes. This is shown to result from the distinct Fourier spectra of the two periodic structures, which differ in both the magnitude and the harmonic content of their reciprocal lattice components. Full article

With the rapid expansion of rural tourism in China, high-quality development has become a key concern for academics and policymakers. Existing studies have focused primarily on economic and industrial growth, with limited attention paid to development quality from the perspective of resident well-being. Using panel data from 30 Chinese provinces from 2012 to 2022, this study establishes a multidimensional evaluation framework for high-quality rural tourism. We employed the entropy weight method, Theil index, and quadratic assignment procedure analysis to examine its level, regional differences, and driving factors. The findings revealed that: (1) the overall level of rural tourism development remained relatively low but rose steadily from 0.064 (2012) to 0.150 (2022) (134.38% cumulative growth), driven by supply-side improvements and demand-side expansion. (2) Pronounced regional inequalities existed: eastern provinces had higher overall levels but larger internal gaps, whereas central/western provinces had lower overall levels but smaller internal differences, with intra-regional disparities accounting for over 66% of the national inequality. (3) The tourism market and transportation were universal key drivers, but the underlying mechanisms differed: the ecological environment exerted greater influence in the east, while public services and living standards were more critical in the central/western regions. By incorporating resident well-being into a systemic analytical framework, this study reconceptualizes high-quality rural tourism as an adaptive socio-ecological system shaped by multilevel interactions among the economy, society, and the environment. The results provide empirical evidence and systemic governance insights for promoting balanced and sustainable rural tourism development. Full article

Metabolic reprogramming is a core hallmark of malignancy, enabling tumor cells to sustain rapid proliferation, evade immune elimination, and develop resistance to therapy. Although a wide range of plant-derived phytochemicals exhibit anticancer activity with comparatively low toxicity, their capacity to disrupt specific metabolic dependencies exploited by tumors has not been comprehensively synthesized. This review brings together current mechanistic evidence showing how major phytochemical classes, including polyphenols, terpenes and terpenoids, glucosinolates, and alkaloids, interfere with pathways central to tumor metabolic fitness, such as aerobic glycolysis, pentose phosphate pathway flux, mitochondrial substrate oxidation, glutamine dependence, and redox homeostasis. It further introduces a pathway-focused framework that links phytochemical mechanisms to quantifiable metabolic outcomes and highlights their potential to remodel the tumor microenvironment by altering nutrient competition, oxidative stress responses, and hypoxia-driven signaling. Key barriers such as poor systemic bioavailability, rapid metabolic degradation, and limited tissue penetration are assessed alongside emerging formulation and delivery strategies designed to enhance therapeutic exposure while preserving low-toxicity profiles. Mapping these mechanistic insights onto clinical development needs allows prioritization of specific phytochemical-metabolic pathway pairs with the strongest potential for translation. This positions plant-derived metabolic disruptors as promising candidates for next-generation, low-toxicity anticancer therapies that strategically exploit defined metabolic vulnerabilities. Full article

The remarkable ecological success of fungi is supported by their capacity for rapid and often reversible molecular responses to fluctuating environments. While conventional evolutionary theory has largely emphasized mutation and selection as central drivers of adaptation, many environmentally responsive fungal traits are also shaped by molecular processes that generate reversible phenotypic variation on ecological or developmental timescales. This review synthesizes current knowledge on reversible genetic and epigenetic mechanisms underlying fungal phenotypic plasticity by integrating insights from programmed genetic rearrangements such as mating-type switching, transposable element activity, variation in tandem repeats and the behavior of accessory chromosomes, together with dynamic epigenetic processes including histone modifications, DNA methylation, chromatin remodeling and RNA mediated regulation. Together, these mechanisms form an interconnected framework that enables rapid and, in many cases, reversible phenotypic diversification, although their consequences range from transient regulatory shifts to partially or fully irreversible sequence-level changes. We highlight the molecular machinery that governs reversibility and its evolutionary implications for fungal pathogenesis, symbiosis, and biotechnology. By uniting genetic and epigenetic perspectives, this review advances a holistic framework in which reversibility is treated as a key property of fungal phenotypic plasticity, helping fungi balance stability with flexibility under environmental challenge. Understanding these mechanisms provides new insights into fungal evolution, and opens new avenues for antifungal intervention and the rational design of industrially valuable fungal strains. Full article

The rise of generative artificial intelligence (GenAI) is creating new opportunities for assessment design in universities, particularly in subjects that emphasize analytical and creative skills. This paper introduces the Educator–GenAI Partnership Model, an iterative five-stage model that helps educators create assessments that foster higher-order thinking (HOT). The model is grounded in constructive alignment and Bloom’s taxonomy, with a central emphasis on preserving human oversight to ensure educators retain control over assessment validity, academic integrity, and the ethical use of AI. The model maps out the unique strengths and responsibilities of both educators and GenAI, showing how each plays a distinct role in the assessment design process. It illustrates how GenAI can support the rapid generation of assessment tasks and marking rubrics, while positioning educators as critical decision-makers who only review, adapt, and iteratively refine AI-generated outputs to ensure alignment with higher-order learning outcomes. Overall, this paper presents a structured and practical model for utilizing GenAI responsibly in assessment design, thereby strengthening academic rigor while enhancing efficiency for educators. Full article

Infectious bursal disease virus (IBDV) is an immunosuppressive pathogen posing a major threat to poultry health worldwide. Its marked phenotypic variability is driven by the rapid evolution of its double-stranded RNA genome, primarily achieved through mutation and reassortment. Although extensive evidence has been generated on molecular determinants of antigenicity and pathogenicity, interpretation is often hindered by heterogeneity and lack of systematicity. This scoping review synthesizes over 35 years of research on amino acid positions influencing IBDV phenotype. A total of 62 studies reporting 107 functionally relevant sites were identified and critically appraised based on evidence type, methodological approach, and ability to infer causality. The results confirmed the central role of VP2, particularly its hypervariable region, while also highlighting the increasingly recognized contribution of other viral proteins. Despite good agreement, comparability across studies was limited by substantial heterogeneity in experimental design and the frequent focus on partial genomic regions. Notably, some molecular markers were context-dependent or inconsistently associated with phenotypic outcomes, underscoring the need for proper interpretation of molecular determinants and for more standardized and comprehensive approaches, including full-genome analyses and reverse genetics. Overall, these findings provide a valuable framework for enhancing molecular diagnostics and supporting the rational design of next-generation vaccines. Full article

Plant disease diagnosis in real-world agricultural environments is challenged by data scarcity, domain shift, privacy constraints, and limited edge-device resources. This paper proposes FMEL-FSDA, a Federated Multimodal Edge Learning framework with Few-Shot Domain Adaptation for robust field-based plant disease recognition. The framework integrates attention-based RGB–text feature fusion, privacy-preserving federated learning, rapid few-shot personalization, and uncertainty-aware inference within an edge-efficient architecture. Federated training enables collaborative learning across distributed farms without sharing raw data, while few-shot adaptation allows fast deployment to new regions using only 1–10 labeled samples per class. Experiments on the PlantWild in-the-wild dataset show that FMEL-FSDA outperforms centralized, federated, and few-shot baselines, achieving 93.78% accuracy, 93.33% F1-score, and 0.97 AUC. The model maintains strong performance under privacy mechanisms such as gradient perturbation and secure aggregation, reduces communication overhead by up to 4×, and supports low-latency edge inference. Uncertainty estimation and Grad-CAM-based explainability further enhance reliability by identifying low-confidence cases and highlighting disease-relevant regions. Overall, FMEL-FSDA offers a scalable, privacy-aware, and field-ready solution for intelligent plant disease diagnosis in precision agriculture. Full article

Light hydrocarbons in shale oil readily volatilize during conventional coring, surface handling, storage, and laboratory preparation. The resulting evaporative loss causes systematic underestimation of Rock-Eval S₁ peak (free hydrocarbons measured by programmed pyrolysis), which can bias oil-bearing evaluation, sweet-spot delineation, and resource assessment. Here we investigate Chang 7₃ lacustrine shale oil in the Ordos Basin (China) using frozen cores recovered by pressure-retained coring from four wells. Time-series Rock-Eval pyrolysis and thermal desorption–gas chromatography (TD–GC) were used to quantify the magnitude, temporal evolution, and practical equilibrium time of light-hydrocarbon loss and to establish a practical restoration model. S₁ decreases with storage time and exhibits a clear two-stage behavior. Shale shows a rapid-loss stage during 0–90 days, followed by a practical equilibrium stage after 90 days (S₁ change less than 5%). Sandstone interbeds lose light hydrocarbons faster and more completely, reaching practical equilibrium after 60 days. TD–GC indicates that the lost fraction is dominated by n-alkane components lighter than C₁₃, with gaseous hydrocarbons showing the greatest depletion; medium and heavy fractions decrease modestly. Loss is coupled with progressive desorption from kerogen and clays, leading to enrichment of heavier components in the residual free hydrocarbons and a shift of the modal carbon number toward higher values. At the shale equilibrium time, total organic carbon (TOC) and vitrinite reflectance (R_o) jointly control the restoration factor K. We propose a two-parameter restoration model: K = (0.4024·ln (TOC) + 0.821)·(0.652·R_o + 0.4292). Applying the model to more than 50 conventionally cored wells reveals that the Qingyang–Zhengning area in the southwestern basin is the principal enrichment zone of original free hydrocarbons, followed by the Jiyuan area in the north and the Huachi area in the central basin, whereas the eastern basin is relatively depleted. The workflow provides a robust and transferable approach for correcting S₁ and improving shale-oil evaluation in lacustrine systems. Full article

Rapid urbanization has led to a significant increase in land use carbon emission (LCE), putting great pressure on ecological security. The coupling relationship between LCE and the ecological security index (ESI) is the key to sustainable development. Based on land use/cover change (LUCC) and Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) data, the LCE of the Jilin Border Cities (JLBCs) from 2013 to 2023 was estimated. Twenty-seven indicators were selected from both natural and socioeconomic aspects to evaluate the ESI using the Driving forces–Pressure–State–Impact–Response–Management (DPSIRM) model. The spatial interaction between LCE and ESI was analyzed using the coupling degree model and spatial autocorrelation. The results show that from 2013 to 2023, the main LCE areas in the JLBCs were concentrated in central urban districts, while the total LCE remained negative but exhibited a clear upward trend. The ESIs in Tonghua City and Baishan City have continued to improve, but those in Yanbian Autonomous Prefecture have gradually deteriorated, with ecological security warnings intensifying progressively toward the east. The spatial variation in the LCE–ESI coupling degree is significant, predominantly exhibiting low coupling with differences across scales. Within the study area, coupling degree shows a strong positive correlation, revealing distinct spatial clustering patterns dominated by low clusters and cold spots. Future efforts should focus on promoting low-carbon development models, strengthening protection and restoration, while implementing targeted measures to enhance the overall ecology of JLBCs. Full article

This study examines the evolution of the scientific literature on mining and heavy metals, with a particular focus on biosanitary risks associated with childhood exposure. The research integrates a systematic literature review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, combined with a bibliometric analysis of Scopus-indexed publications, international epidemiological data, and an evaluation of the socio-environmental context in Ecuadorian mining regions. The PRISMA-based screening process was applied to identify, filter, and select relevant peer-reviewed studies, enabling the delimitation of a focused corpus of literature, with particular attention given to scientific contributions produced by Latin American researchers and institutions. The results reveal a significant concentration of knowledge production among a limited number of countries and institutions, the dominance of English as the main language of scientific communication, and the centrality of journals in environmental sciences and toxicology. While notable progress has been made in identifying contaminants and exposure pathways, governance structures, territorial disparities, and policy implementation processes remain insufficiently explored. In Ecuador, the rapid growth of mining concessions in ecologically sensitive zones presents potential threats to children’s neurocognitive development, highlighting the urgent need for ongoing surveillance, biomonitoring programs, and preventive public health measures. The study emphasizes the importance of strengthening regional research capacity and fostering more equitable international scientific collaborations to ensure that knowledge production is responsive to local contexts and effectively safeguards vulnerable populations. Full article

Chikungunya virus (CHIKV) infection presents a wide spectrum of clinical outcomes, ranging from mild self-limiting disease to severe and fatal manifestations, which are influenced by both host and viral factors. Animal models are essential for elucidating CHIKV pathogenesis and for preclinical evaluation of antiviral strategies; however, a well-characterized model evaluating the effect of different viral doses in AG129 mice remains limited. In this study, we investigated the clinical, virological, and pathological outcomes of CHIKV infection in male AG129 mice inoculated intraperitoneally with different viral doses (10, 100, and 1000 PFU/mL) of a Brazilian strain belonging to the East/Central/South African (ECSA) lineage. Lower-dose inoculation (10 PFU/mL) resulted in a milder disease course, characterized by transient viremia, limited tissue viral dissemination, minimal histopathological alterations, partial survival, and viral clearance. In contrast, higher doses (≥100 PFU/mL) led to rapid systemic viral dissemination, severe histopathological damage in the spleen, liver, and kidneys, and uniform lethality. Viral RNA was detected in serum and multiple organs in a time-dependent manner, with limited differences among inoculum doses in most tissues. Notably, dose-related differences were observed in specific compartments and time points, particularly in hind-limb muscles at early time points and in serum at later stages. Full article

Cutaneous melanoma is the most lethal form of skin cancer because of its aggressiveness, rapid metastasis, and high therapeutic resistance. The 2018 World Health Organization (WHO) classification emphasized that melanoma comprises distinct subtypes defined by cumulative sun damage, site of origin, and molecular characteristics, which explain differences in mutational burden, immunogenicity, and treatment response. Immunotherapy with anti-PD-1 therapy such as nivolumab and pembrolizumab changed the therapeutic landscape by restoring CD8+ T-cell activity and improving survival. Still, many patients show primary or acquired resistance influenced by low PD-L1 expression, loss of antigen presentation, tumor metabolic plasticity, and an immunosuppressive microenvironment. Mitochondria are central to this process. They regulate ATP generation through oxidative phosphorylation (OXPHOS), redox control, apoptosis, and the metabolic programming needed for T-cell activation. In the tumor microenvironment (TME), hypoxia, nutrient restriction, and PD-1 signaling reduce mitochondrial biogenesis, increase fission and reactive oxygen species (ROS) accumulation, and lead to exhaustion and impaired effector function. Moreover, tumor cells outcompete immune cells for key nutrients such as glucose and glutamine, while increased lactate production and extracellular acidosis further suppress mitochondrial respiration in T cells. Strategies to overcome resistance include restoring oxidative metabolism, activating PGC-1α, supplying metabolic substrates, and combining checkpoint blockade with inhibitors of glycolysis or glutaminolysis to enhance the immune response. Full article