Search Results (516)

Butterfly elevational distribution patterns are modulated by temperature stratification, vegetation composition, butterfly functional traits, and anthropogenic disturbances. To explore the elevational patterns of butterfly α- and β-diversity and their driving mechanisms on Mount Gongga, we established 18 standardized 1000 m transects at 200 m intervals across an elevational range of 1000–4500 m. Butterfly species richness and abundance were systematically surveyed using the line-transect method. The results indicated that both butterfly species richness and abundance significantly decreased with increasing elevation. Notably, butterfly β-diversity exhibited a distinctive nonlinear trimodal pattern along the elevational gradient, with three peak values occurring at 1900–2300 m, 3500–3900 m, and 4300–4500 m. This pattern differs substantially from the monotonically decreasing or unimodal β-diversity trends widely reported for most mountain insect communities. Vegetation ecotone effects, habitat heterogeneity differentiation, elevational species turnover, and topographic microclimate heterogeneity collectively drive this unique distribution pattern. Based on these findings, we propose targeted conservation recommendations: (1) prioritize the protection of key vegetation transition zones; (2) sustain vegetation integrity to guarantee sufficient food and habitat resources for butterflies; (3) address climate change threats to conserve high-elevation endemic butterfly species; (4) develop long-term monitoring programs to improve regional biodiversity conservation systems. Full article

Wind is an important abiotic factor that may influence predator–prey interactions. In this paper, we propose and analyze a stochastic predator–prey model in which the predator attack rate is described by a unimodal function of a fixed wind-intensity index. We establish the global existence, uniqueness, and positivity of solutions, together with stochastic ultimate boundedness, and derive a sufficient condition for the existence of a unique ergodic stationary distribution. A key analytical feature is that the Foster–Lyapunov recurrence argument is completed without quadratic predator self-limitation by exploiting the negative contribution generated by linear predator mortality. The resulting condition $\lambda >0$ incorporates effective predation, density dependence, wind modulation, predator mortality, and population-level environmental noise, and is a sufficient rather than necessary condition. Numerical parameter sweeps based on the complete expression for $\lambda$ and simulations using a logarithmic Euler–Maruyama scheme illustrate parameter-specific changes in the sufficient-condition quantity and in the post-burn-in empirical population distributions. Full article

Context: Forage bermudagrass (Cynodon dactylon) is widely used in warm-season livestock production systems because of its high productivity and adaptability. However, systematic evaluation of forage-type germplasm remains limited, restricting the identification of superior breeding materials. Aims: This study aimed to evaluate phenotypic variation, identify key yield-related traits, and identify high-performing forage bermudagrass germplasm with contrasting interannual phenotypic responses derived from a ‘Wrangler’ × ‘CD-21’ hybrid population. Methods: Two evaluation populations were established. A single-genotype population of 621 individuals was used to assess plant and canopy height variation, whereas 16 representative entries were evaluated for biomass yield and major agronomic traits during 2024–2025. Frequency distribution, principal component, correlation, and path analyses were conducted. Key results: Stem height and canopy height showed unimodal, approximately normal distributions, indicating continuous phenotypic variation and supporting their characterization as quantitative traits. Biomass yield was positively associated with stem height (r = 0.79), canopy height (r = 0.82), and internode length (r = 0.63). Path analysis indicated that stem height had the largest estimated direct effect (β = 0.45) on biomass yield within the proposed path model. Multivariate analyses revealed distinct phenotypic differences among entries and years, allowing classification into high-performing, environmentally responsive, and leaf-structure efficient groups. Conclusions: Stem height, canopy height, and internode length were identified as key traits associated with forage biomass production. Integrating multivariate and path analyses effectively differentiated forage bermudagrass germplasm based on yield performance and agronomic traits. Implications: The identified germplasm and trait relationships provide useful information for further breeding evaluation and selection decisions and support the development of improved forage bermudagrass cultivars. Full article

The population genetic diversity and demographic history of Hypomeces pulviger in Thailand were examined based on mitochondrial cytochrome c oxidase subunit 1 (CO1) and 16S ribosomal DNA (16S rDNA) sequence data. A total of 171 and 104 individuals from multiple populations were analyzed using CO1 and 16S rDNA sequences, respectively. The CO1 sequence dataset revealed high haplotype diversity (Hd = 0.999) and moderate nucleotide diversity (Nd = 0.0323), whereas the 16S rDNA showed lower diversity (Hd = 0.750, Nd = 0.0026). Population structure analyses showed low to moderate differentiation in CO1 sequences with a significant isolation-by-distance pattern, suggesting distance-limited gene flow, while 16S rDNA sequences showed weaker structure. Neutrality tests and mismatch distribution analyses supported a recent population expansion, as indicated by significantly negative Fu’s Fs and a unimodal distribution. Haplotype network and phylogenetic analyses further demonstrated greater resolution in the CO1 gene compared to the 16S rRNA gene. Collectively, H. pulviger populations in Thailand are genetically diverse, connected, and expanding, likely facilitated by both natural dispersal and agricultural activities. These findings provide important insights for understanding pest dynamics and developing effective management strategies. Full article

In this paper, we introduce a new three-parameter lifetime distribution that is obtained via a power transformation of the modified bimodal exponential model. The inclusion of an additional shape parameter significantly enhances the flexibility of the baseline distribution, allowing it to capture a wide range of distributional characteristics, including skewness, heavy tails, and varying hazard rate shapes such as increasing, decreasing, and non-monotonic forms. Several important structural properties of the proposed model are derived, including explicit expressions for the probability density function, cumulative distribution function, moments, and moment generating function. Entropy measures such as Rényi entropy, Shannon entropy, and cumulative residual entropy are also obtained. Key reliability characteristics, including the survival function, hazard rate function, cumulative hazard function, reversed hazard rate, and mean residual life function, are investigated in detail. A theoretical result on the modality of the distribution is established, demonstrating its ability to exhibit both unimodal and bimodal shapes. Parameter estimation is carried out using maximum likelihood estimation along with several alternative methods. A comprehensive simulation study is conducted to evaluate the performance of the estimators under different parameter settings. Finally, the applicability and effectiveness of the proposed distribution are demonstrated through the analysis of real datasets from reliability and environmental studies. Comparative results based on goodness-of-fit measures indicate that the proposed model provides a superior fit compared to several existing competing distributions. Full article

Reliable scene understanding under open-world conditions requires intelligent perception systems to accurately recognize known semantic categories while remaining robust to out-of-distribution (OOD) inputs, distribution shifts, and uncertain environmental conditions. This challenge becomes increasingly important for resource-constrained edge intelligence, where lightweight models are expected to provide reliable predictions without sacrificing computational efficiency. Although knowledge distillation has achieved remarkable success in compressing deep neural networks, existing methods primarily transfer classification semantics and often neglect the uncertainty representations that are critical for reliable open-set perception. To address this issue, we propose Residual Feature-driven Knowledge Distillation (RFKD), a lightweight uncertainty-aware distillation framework for reliable open-set scene understanding under distribution shift. Instead of directly distilling output confidence or energy scores, RFKD reconstructs uncertainty within the student’s latent feature space through a compact residual uncertainty branch. The proposed framework combines confidence-aware supervision, relational uncertainty distillation, and energy-guided relative ordering to preserve teacher-induced uncertainty geometry while enabling the student to learn discriminative feature-level uncertainty representations. The present study is evaluated on unimodal image data and does not claim empirical validation for multimodal perception. Extensive experiments on CIFAR-100 using multiple OOD benchmarks demonstrate that RFKD consistently improves uncertainty estimation while maintaining high computational efficiency. Compared with the ResNet-50 Teacher (Energy), RFKD increases the average AUROC from 0.7793 to 0.8446 while reducing the model size from 23.71 M to 11.29 M parameters and computational complexity from 1.31 G to 0.56 G FLOPs; the ImageNet-style student baseline obtains an AUROC of 0.7528. A score-specific sensitivity analysis shows that the energy detector is strongest when the auxiliary ordering score uses the residual branch alone, whereas moderate coupling with the student’s log-sum-exp potential improves the standalone OOD head. These results demonstrate that explicitly modeling representation-level uncertainty offers an effective and efficient solution for reliable scene understanding, providing a practical reliability enhancement for future intelligent perception systems operating in open and dynamic environments. Full article

In this study, we assessed the impact of prior-induced regularization using six real datasets from wheat, rice, and potato, spanning 107–758 genotypes, 2–12 environments, 1–18 traits, and 2744–108,024 molecular markers. Two modeling scenarios were evaluated: (i) unimodal genomic prediction based solely on marker information and (ii) multimodal (multi-component) prediction integrating genomic, environmental, and genotype-by-environment (G × E) effects. Predictive performance was evaluated using Pearson’s correlation (COR) and normalized root mean squared error (NRMSE) under 10 repeated random 50% training–50% testing partitions, representing prediction of untested lines in tested environments. Bayesian genomic prediction (BGP) relies on prior distributions to regulate shrinkage and stabilize inference in high-dimensional settings. We evaluated whether predictive performance was driven primarily by the type of Bayesian prior or by the presence of effective prior-induced regularization. Across most datasets, regularized Bayesian models achieved higher predictive correlations and markedly lower NRMSE than the weakly regularized or unregularized baseline. Differences among regularized prior families were generally modest, whereas weakening or removing regularization frequently produced unstable estimates and inflated prediction error. Predictive results were obtained for both winter-wheat datasets as well as for the rice, potato, and DMario datasets. In multimodal analyses, models with coherent regularization across genomic, environmental, and genotype-by-environment components were generally more accurate and stable than configurations in which regularization was absent or weakened in key components. Rice_Kim_2020 was an informative exception in which the baseline remained competitive. These results show that the principal empirical contrast is the presence versus absence of effective prior-induced regularization, rather than a universal ranking of Bayesian prior families. Appropriate regularization should therefore be treated as a central model-design decision in genomic prediction. Full article

The complexity of micrometer-scale pore-throat structures in sandstone reservoirs strongly controls the occurrence state and mobilization degree of residual oil after water-flooding. To clarify the differences in residual oil occurrence between pure oil-zone and transition-zone reservoirs and their microscopic controlling mechanisms, sandstone samples were collected from the SII oil layer group, which belongs to the Upper Cretaceous Yaojia Formation, in the Nanqi area of the Daqing Oilfield, northern Songliao Basin, NE China, and were investigated. Mercury intrusion capillary pressure (MICP), two-dimensional nuclear magnetic resonance (2D NMR), laser scanning confocal microscopy (LSCM), micro-computed tomography (micro-CT), X-ray diffraction (XRD), wettability measurement and fractal analysis were integrated to systematically characterize the pore-throat architecture, mineral composition, seepage capacity, and residual oil occurrence of the two reservoir types. The results show that the pore-throat radius distributions are mainly unimodal. In the pure oil-zone samples, the pore-throat distribution is highly consistent with the corresponding permeability contribution curve, whereas evident deviations occur in some transition-zone samples. Large and medium pore throats exert the most significant control on seepage capacity, and the difference in fractal characteristics is mainly reflected by D1, the fractal dimension of large pore throats. The transition-zone reservoirs generally exhibit moderate to strong water-wet characteristics. Owing to the development of fine pore throats and strong capillary forces, water is prone to retention within pore-throat spaces, resulting in pronounced water-blocking and Jamin effects. After water-flooding, the pure oil-zone reservoirs exhibit lower residual oil saturation, with residual oil occurring mainly in a bound state; in contrast, the transition-zone reservoirs show higher residual oil saturation and relatively high proportions of free and semi-bound residual oil. Mineral composition further modifies pore-throat complexity and residual oil occurrence. D1 is negatively correlated with feldspar content, indicating that increased feldspar content helps improve the pore-throat structure, but positively correlated with clay mineral content, suggesting that clay minerals enhance structural complexity. In the transition-zone reservoirs, kaolinite and illite–smectite mixed-layer minerals are relatively well developed. Their velocity-sensitive and water-sensitive effects readily induce pore-throat blockage and increased flow resistance, which are important causes of residual oil enrichment and difficult oil mobilization in the transition zone. Full article

Evaluating the sealing integrity of caprocks is critical for ensuring the long-term safety and containment efficiency of geological hydrocarbon reservoirs and CO₂ storage systems. In this study, we evaluated the caprock sealing capacity of the South Sea continental shelf using drill cutting samples collected from six wells across four structural blocks. Representative caprock intervals, consisting primarily of fine-grained sedimentary rocks, were identified based on well data and lithofacies information. Mercury Injection Capillary Pressure (MICP) analyses were performed to characterize pore structure and capillary sealing behavior. Results indicate that nanopores (<1 μm) dominate the pore system; however, pore size distributions exhibit significant heterogeneity. While B well samples displayed unimodal nanopore distributions, other wells showed bimodal or broad multiscale structures. As a result, MICP-derived Hg-air breakthrough pressures (P_b) varied considerably, ranging from 75 to 283 MPa. Notably, samples G-1 and J5-4 exhibited sealing capacities capable of retaining CO₂ column heights exceeding 5052 m, whereas sample J1-1 showed the lowest sealing performance. In the B well, a clear depth-dependent trend was observed: as depth increased from 2480 m to 3685 m, the critical pore diameter decreased from 13.66 nm to 7.57 nm, and breakthrough pressure increased from 95 MPa to 171 MPa. Subsequent quantitative XRD analysis, corrected for drilling-induced contamination, revealed that these deeper intervals are characterized by clay-rich (50.85–63.19%) and relatively ductile mineralogical compositions. These findings suggest that burial-related compaction within a consistently clay-rich, relatively ductile matrix may contribute to pore-throat refinement and enhanced relative capillary sealing capacity in the B well. Overall, the caprocks of the South Sea continental shelf show significant potential for geological hydrocarbon and CO₂ storage, though the observed spatial and depth-dependent heterogeneity underscores the necessity of well-specific site characterization. Full article

The degree of polarization is usually obtained from the coherency matrix or, equivalently, from the mean Stokes vector of a partially polarized optical field. Here, we adopt a complementary geometric viewpoint by representing normalized local Stokes vectors as random directions on the Poincaré sphere. When these directions are described by an effective unimodal von Mises–Fisher distribution, the concentration parameter gives a direct one-to-one description of the degree of polarization through the mean resultant length. This formulation does not define a new independent polarization observable. Instead, it gives the degree of polarization a rotation-invariant information-theoretic meaning, expressed in terms of directional concentration and angular disorder. Within this framework, we derive closed-form expressions for the differential entropy of the von Mises–Fisher distribution and for the Kullback–Leibler divergence between two directional polarization states. The symmetrized divergence further incorporates both differences in concentration and relative orientation on the Poincaré sphere. We also discuss the assumptions, range of validity, and limitations of the single-vMF model, particularly in relation to Gaussian field statistics and more general directional models needed for anisotropic or multimodal polarization fluctuations. Overall, this formalism establishes a model-based theoretical framework for entropy and divergence descriptors of unimodal directional polarization and suggests natural extensions toward mixtures of vMF, Bingham, or Kent distributions. Full article

Saxicolous lichens are crucial elements of alpine ecosystems and are involved in soil formation, rock weathering, nutrient cycling, and environmental monitoring. However, little is known about their distribution patterns and diversity on the eastern Pamir Plateau of China. This study looked at the variety and elevational distribution of saxicolous lichens in China’s eastern Pamir Plateau’s Taxkorgan Nature Reserve. Six transects spanning an elevational range of 3500–4500 m were used for field studies in July and August of 2025. Stratified sampling was used to gather lichen specimens, which were then identified by morphological, anatomical, chemical (thin-layer chromatography), and molecular investigations. Lichens communities’ similarity across altitudes was evaluated using Sørensen’s index, and diversity indices such as Simpson, Shannon–Wiener, and Pielou’s consistency were computed. A total of 69 saxicolous lichen species from 12 families and 27 genera were identified. With 95.6% of all species, crustose lichens predominated, whilst foliose and fruticose forms were uncommon. Acarosporaceae and Megasporaceae were the most species-rich families, accounting for over half of total recognized species. In the study region, Aspicilia and Acarospora dominated at the genus level. Saxicolous lichen species richness exhibited a unimodal elevational pattern, peaking at 4101–4300 m with pronounced community turnover across altitudes, as supported by Sørensen similarity values (0.253–0.561). Additionally, substrate type affected lichen distribution, with siliceous rocks hosting richer lichen communities than calcareous substrates. In general, the richness and distribution of saxicolous lichens in the alpine ecosystems of the eastern Pamir Plateau are mostly determined by elevation and rock type. This work provides essential baseline data for lichen biodiversity in the region and highlights the potential use of lichens as bio-indicators for monitoring environmental change in high-mountain ecosystems. Full article

Multimodal entity linking (MEL) grounds entity mentions in text-image contexts to entries in a structured knowledge base; however, most existing systems still decompose a multimodal document into independent mention-level decisions. This formulation overlooks a central tension of real-world MEL: the evidence needed to disambiguate an ambiguous mention is often distributed across co-occurring mentions, visual context, and cross-modal consistency, rather than being contained in the mention itself. To address this limitation, we propose Collaborative Entity Linking through Multichannel Interaction (CELMI), a four-channel framework that jointly models textual semantics, visual perception, cross-modal alignment, and inter-mention collaboration. CELMI employs dual-level textual alignment, text-guided visual gating, learned cross-modal projection, and attention-based entity graph propagation. To stabilize joint optimization, we further introduce a multi-channel consistency objective that combines per-channel contrastive losses with an overall ranking loss, reducing channel dominance and representation collapse. Among conventional non-LLM/VLM MEL models, CELMI achieves the strongest MRR and Hits@1 performance on WikiMEL, RichpediaMEL, and WikiDiverse, with Hits@1 scores of 89.03% on WikiMEL and 83.02% on RichpediaMEL; LLM/VLM systems remain stronger on WikiDiverse, positioning CELMI as a lightweight complement. Progressive stress ablation shows a 38.50 percentage-point absolute Hits@1 drop when the architecture is reduced to a single unimodal endpoint, confirming that the gains arise from synergistic channel interaction rather than isolated module effects. Full article

Ribbed Smoked Sheet (RSS) rubber production in southern Thailand relies extensively on rubber-wood combustion, potentially generating substantial emissions of fine particulate matter and polycyclic aromatic hydrocarbons (PAHs). Despite the economic importance of this sector, systematic characterization of biomass-derived PAHs under tropical monsoonal and coastal conditions remains limited. This study investigates the particle size distribution, concentration levels, seasonal variability, and atmospheric dynamics of PAHs associated with RSS production in Chumphon Province, Thailand. Size-segregated particulate matter was collected using an eight-stage Andersen cascade impactor at two contrasting sites during a seven-month monitoring period from March to September 2025, covering the transition from the late dry/summer season to the rainy season in southern Thailand. Fifteen priority PAHs were quantified by high-performance liquid chromatography with fluorescence detection. Results indicate that emissions from rubber-wood combustion inside smokehouses exhibit a unimodal distribution dominated by submicron particles (MMAD = 0.85 µm; GSD = 2.71). Ambient aerosols displayed a bimodal structure, with an accumulation-mode peak (~0.6 µm) associated with combustion processes and a coarse-mode peak (~4 µm) linked to mechanical and marine aerosol sources. Particle-bound PAHs were predominantly associated with fine particles (~0.59 µm), although seasonal hygroscopic growth under high humidity shifted modal diameters toward ~1.8 µm during the rainy season. PAH profiles were dominated by 3–4 ring compounds characteristic of biomass combustion. Total PAH concentrations exhibited a strong positive correlation with monthly RSS production, while precipitation demonstrated an exponential scavenging effect. Monsoonal circulation and sea spray aerosol (SSA) interactions were identified as key regulators of gas–particle partitioning, transport pathways, and removal efficiency. The findings reveal that the coastal atmosphere of southern Thailand functions as a dynamic multiphase system in which emission intensity, hygroscopic particle growth, monsoonal transport, and wet deposition collectively govern PAH behavior. This study provides the first integrated assessment linking rubber-sheet production dynamics to size-resolved PAH distributions under tropical coastal conditions and offers a scientific foundation for emission mitigation strategies in biomass-dependent agro-industrial regions. Full article

Alternaria alternata often causes preharvest potato early blight and postharvest tuber rot, which can result in substantial yield losses. Demethylation inhibitors (DMIs) are widely used to control Alternaria diseases. However, the underlying resistance risk remains poorly understood. In this study, 114 A. alternata isolates from five major potato-producing regions in Shandong, China, were evaluated for sensitivity to four DMIs (mefentrifluconazole, prothioconazole, tebuconazole, and difenoconazole). The mean EC₅₀ values were 0.622, 6.053, 4.763, and 0.651 mg·L⁻¹, respectively. The Shapiro–Wilk test confirmed unimodal sensitivity distributions, allowing these mean EC₅₀ values to serve as baseline sensitivities. Two-year, two-location field trials demonstrated good control efficacy for all fungicides, with mefentrifluconazole exhibiting the highest efficacy. Three resistant mutants produced by artificial selection in the laboratory exhibited 3.78-, 28.06-, and 15.73-fold higher EC₅₀ values and showed fitness costs, including reduced or comparable mycelial growth, sporulation, and spore germination, pathogenicity similar to that of the parental strain, and lower temperature adaptability. By establishing the first baseline sensitivity of A. alternata from potato to these four DMI fungicides and assessing the resistance risk of mefentrifluconazole, this study provides a basis for rational fungicide application, resistance management, and future field resistance monitoring. Full article

To address the weak interfacial transition zone and insufficient mechanical properties of recycled aggregate pervious concrete, this study proposes a dual modification strategy using basalt fibers and ultra-fine mineral powder. The macroscopic mechanical and hydraulic properties of the material were analyzed through orthogonal experiments. Techniques including X-ray diffraction, scanning electron microscopy, and micro-computed tomography were employed to systematically reveal the microstructural evolution and internal pore network topology of the modified system. Based on range analysis of mechanical stiffness and drainage efficiency, the optimal mix proportions were determined as 5–10 mm aggregate, a water–cement ratio of 0.31, and a fiber content of 0.50%. Microscopic tests confirm that the pozzolanic reaction of ultra-fine mineral powder increases matrix density and enhances the shear bond strength between fibers and the cement paste, enabling the physical bridging effect of basalt fibers. The dual modification exhibits a synergistic effect on load-bearing capacity and crack resistance. CT scan results show that the internal pore cross-sectional area follows a unimodal skewed distribution, with the characteristic distribution peak located at 3.5 mm². This homogeneous microporous network limits the critical defect size, optimizing the stress transfer path while ensuring fluid transport. Full article