Search Results (217)

The wild yak (Bos mutus) is a flagship species on the Qinghai–Tibet Plateau, possessing significant ecological functions and conservation value. Using single-nucleotide polymorphism markers from whole-genome resequencing, we systematically analyzed golden wild yak (n = 37), common wild yak (n = 106), and domestic yak (Bos grunniens) (n = 20) to characterize the population genetic structure and adaptive selection signals in the golden wild yak. Genetic diversity analyses revealed that the golden wild yak had the lowest nucleotide diversity (π = 0.00148) and the highest inbreeding coefficient (F_Hom = 0.043). Population structure analyses integrating principal component analysis, phylogenetic tree, and ancestral component clustering indicated that the golden wild yak formed a relatively independent evolutionary lineage. However, its genetic differentiation from sympatric common wild yak population was limited (fixation index = 0.031). Selective sweep analysis identified a set of candidate positively selected genes in the golden wild yak genome associated with key traits and physiological functions, including coat color (TYRP1), hypoxia adaptation (MYH11, POLQ), reproductive function (SLC9C1, SPAG16, CFAP97D1), and immune response (CASP8, PGGT1B, BIRC6). Overall, our study reveals a distinct genetic background and selection signatures in the golden wild yak and provides genomic insights to inform the conservation and management of the wild yak. Full article

The rising demand for convenient, nutritious foods necessitates improved freeze–thaw (F-T) stability in frozen fish balls; however, traditional thermal processing fails to prevent moisture loss, textural degradation, and oxidation. Therefore, this study systematically investigated the effect of ultra-high pressure (UHP) treatment on the quality of golden pomfret fish balls (Trachinotus ovatus) using two-step heating as a control during the F-T cycles. The results showed that compared to two-step heating, UHP significantly reduced the thawing loss (0.68 times) and centrifugal water loss (2.43 times) by enhancing the water-binding capacity (15–20%) and forming denser gel networks. Microstructural analysis revealed that UHP resulted in a more compact internal structure, reduced porosity, altered ice-crystal geometry, and a slower recrystallization rate of the fish balls. Furthermore, UHP effectively reduced protein oxidation (34.53% lower carbonyl increase) and lipid peroxidation (15.6% lower TBARS value) after five F-T cycles compared to the control. Correlation analysis confirmed the dual role of UHP in the regulation of oxidative and structural stability. These findings provide a new technological approach for processing and storing fish balls. Full article

Despite extensive research on the effect of nitrogen flow rate on titanium nitride (TiN) coating properties, its influence on esthetic and engineering performance through microstructure control remains insufficiently explored. To simultaneously meet the requirements for surface strengthening and decorative esthetics in high-end stainless-steel crafts, TiN coatings were deposited on 304L stainless-steel substrates using multi-arc ion plating. The regulatory mechanisms and synergistic evolution laws of nitrogen flow rates (100, 200, and 300 sccm) on the microstructure, decorative properties (color and gloss), and engineering performance (adhesion strength, hardness, wear resistance, and corrosion resistance) of the coatings were investigated. At a nitrogen flow rate of 200 sccm, the coating exhibited a uniform and dense columnar crystal structure, as well as a saturated golden hue with high surface gloss. Additionally, the film–substrate adhesion, microhardness, tribological properties, and corrosion resistance reached optimal levels. In contrast, excessively low (100 sccm) or high (300 sccm) nitrogen flow rates resulted in coarse particles and blurred grain boundaries owing to uncontrolled droplet ejection or target poisoning, respectively, thereby deteriorating both appearance and engineering performance. These findings can inform the optimization of TiN coatings, enabling the design of surfaces that simultaneously meet esthetic and high-performance engineering requirements. Full article

The volumetric Hirst method is considered a golden standard in aerobiology for determining particle number concentrations of bioaerosols. Using Hirst-type pollen and spore traps on mobile platforms (i.e., aircraft, cars, motorbikes, bicycles or carried by pedestrians) is anticipated to significantly enhance the spatial and temporal granularity of data for bioaerosol monitoring. Mobile sampling promises to enhance our understanding of bioaerosol dynamics, ecological interactions and the impact of human activities on airborne biological particles. In this article, we present the design and test of an airborne Hirst-type volumetric sampler. We followed a structured approach and incorporated the fundamental principles of the original design, while optimizing for size, weight, power and cost. Our portable Hirst-type volumetric sampler (FlyHirst) was attached to an ultralight aircraft, together with complementing instrumentation, and was tested for collection of atmospheric concentrations of pollen, fungal spores and hyphae. By linking the temporal resolution of the samples with the spatial position of the aircraft, using flight time, we calculated the spatial resolution of our measurements in 3D. In six summer flights over Denmark, our study revealed that the diversity of the recorded spores corresponded to the seasonal expectance. Urtica pollen was recorded up to 1300 m above ground (a.g.l.), and fungal spores up to 2100 m a.g.l. We suggest that, based on this proof-of-concept, FlyHirst can be applied on other mobile platforms or as a personal sampler. Full article

This article investigates fundamental inequalities within a golden-like statistical manifold (GLSM) equipped with a semi-symmetric metric connection (SSMC). We explore key geometric and analytical properties, including curvature relations and inequalities analogous to those in classical information geometry. The interplay between the golden-like structure and the SSMC yields new insights into the underlying differential geometric framework. Our results extend known inequalities in the statistical manifold (SM), providing a foundation for further studies in optimization and divergence theory within this generalized framework. Full article

The nutritional value of lipids depends not only on their fatty acid composition but also on their stereospecific positioning on the glycerol backbone. This study investigated the fatty acid composition and sn-2 positional distribution of triacylglycerols (TAG), as well as the composition of major phospholipids in golden pompano (Trachinotus ovatus) juveniles (initial weight: 10 g) fed five diets including graded levels of dietary n-3 highly unsaturated fatty acids (HUFA; 0.64–2.10%) for 56 days. With increasing dietary n-3 HUFA levels, the proportions of eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), docosahexaenoic acid (DHA), and total n-3 HUFA in muscle TAG, phosphatidylcholine (PC), and phosphatidylethanolamine (PE) significantly increased. Phospholipids, especially PC and PE, were preferentially enriched with n-3 HUFA, and the sn-2 positions of TAG showed a significantly increased deposition of DHA and reduced n-6/n-3 ratios. RNA-Seq analysis was performed on muscle tissues of T. ovatus subjected to different dietary n-3 HUFA levels to further investigate the molecular mechanisms of lipid compositional and structural changes. A total of 126,792 unigenes were obtained, of which 47.78% were successfully annotated. KEGG pathway enrichment analysis implicated the glycerophospholipid, glycerolipid, and sphingolipid metabolism pathways in lipid composition and distribution regulation, identifying gpat4, agpat3, agpat8, lpeat1, and lpgat1 as potential regulators. These findings offer insights into lipid remodeling in marine fish and support strategies to enhance aquaculture product quality. Full article

Maneuvering extended object tracking has garnered significant attention owing to the continuous advancements in the resolution capabilities of modern high-precision radar sensors. The efficacy of tracking algorithms for such objects is heavily contingent upon the design of the model set. However, existing methodologies for model set design often yield suboptimal performance when confronted with highly maneuvering extended objects. The expected model augmentation (EMA) algorithm offers a data-driven mechanism for updating the model set in real time. Despite its advantages, the EMA algorithm is constrained by the fixed parameters of its basic models and static transition probabilities between models, thereby limiting its adaptability to extended objects exhibiting complex and dynamic maneuvering behaviors. To address these limitations, this paper proposes a modified variable structure multiple model (VSMM) framework for maneuvering extended object tracking, referred to as the adaptive grid expected model augmentation based on the golden section (GSAG-EMA) algorithm. The approach adaptively adjusts both the model structure and parameters in a grid-based format to accommodate the varying maneuvering patterns. It incorporates both local and global weighting schemes, with two models within the grid based on the golden section. Furthermore, the transition probability matrix is dynamically updated following specific rules, and the execution strategy for each module is determined according to the filtering results. Simulation results under both weak and strong maneuvering scenarios demonstrate that the proposed GSAG-EMA algorithm consistently outperforms the IMM-based, EMA, and AG-BMA algorithms in terms of root mean square error (RMSE) and Hausdorff distance, thereby substantiating its superior tracking performance. Full article

Rapid pressure fluctuations—known as hydraulic transients—occur during valve operations or load changes in turbines and pumps. The presence of biofouling, particularly caused by the golden mussel (Limnoperna fortunei), can intensify these effects and compromise the structural integrity of pressurized systems. This study experimentally evaluated the influence of such biofouling on pressure peaks during transient events in forced conduits. A hydraulic test rig was developed using PVC pipes with nominal diameters of 2½”, 3”, and 4”, tested under both clean conditions and with simulated biofouling printed in 3D, replicating mussel morphology. Results showed that, under the same initial flow rates, pressure peaks in biofouled pipes were significantly higher than in clean ones, especially in smaller diameters. To mitigate structural risks, the downstream shut-off valve closure time was modulated using a needle valve, effectively reducing peak pressures to levels closer to design limits. It is concluded that L. fortunei colonization alters transient hydraulic behavior and should be considered in the design and operation of systems vulnerable to biofouling, particularly in critical infrastructure such as water supply networks and hydroelectric power plants. Full article

Apples and pears are among the most popular and frequently consumed fruits worldwide. The polyphenol and dietary fibre components of these fruits are known to influence the gut microbiota and the subsequent human health outcomes. This study investigated the effects of New Zealand grown apples and pears with differing polyphenol contents on the structure and function of the human gut microbiota. Five apple and two pear cultivars underwent in vitro human digestion and microbial fermentation. Samples taken at 0 and 18 h were analysed for changes in pH, microbial composition, and organic acid production. The change in pH after faecal fermentation was influenced by the type of fruit (apple or pear), with lower pH being observed in the apples. Significant apple or pear cultivar effects were observed for the gut microbiome and organic acid production. The apple cultivar ‘Golden Hornet’ produced the least butyrate and the greatest microbial alpha diversity, while the pear ‘PremP009’ showed greater butyrate production with increases in a butyrogenic species (Acidaminococcus intestini). Further studies are needed to investigate the effect of cultivar and type of fruit on nutrient absorption and microbial fermentation and the impact of these on human health. Full article

Recent advancements have been made in the precise prediction of protein structures within the Protein Folding Problem (PFP), particularly in relation to minimizing the energy function to achieve stable and biologically relevant protein structures. This problem is classified as NP-hard within computational theory, necessitating the development of various techniques and algorithms. Bio-inspired algorithms have proven effective in addressing NP-hard challenges in practical applications. This study introduces a novel hybrid algorithm, termed GRSABio, which integrates the strategies of Jumping Spider Algorithm (JSOA) with the Golden Ratio Simulated Annealing (GRSA) for peptide prediction. Furthermore, the GRSABio algorithm incorporates a Convolutional Neural Network for fragment prediction (FCNN), forms an enhanced methodology called GRSABio-FCNN. This integrated framework achieves improved structure refinement based on energy for protein prediction. The proposed enhanced GRSABio-FCNN approach was applied to a dataset of 60 peptides. The Wilcoxon and Friedman statistics test were employed to compare the GRSABio-FCNN results against recent state-of-the-art-approaches. The results of these tests indicate that the GRSABio-FCNN approach is competitive with state-of-the-art methods for peptides up to 50 amino acids in length and surpasses leading PFP algorithms for peptides with up to 30 amino acids. Full article

This paper explores novel inequalities for statistical submanifolds within the framework of the Norden golden-like statistical manifold. By leveraging the intrinsic properties of statistical manifolds and the structural richness of Norden golden geometry, we establish fundamental relationships between the intrinsic and extrinsic invariants of submanifolds. The methodology involves deriving generalized Chen-type and $\delta (2,2)$ curvature inequalities using curvature tensor analysis and dual affine connections. A concrete example is provided to verify the theoretical framework. The novelty of this work lies in extending classical curvature inequalities to a newly introduced statistical structure, thereby opening new perspectives in the study of geometric inequalities in information geometry and related mathematical physics contexts. Full article

This study investigates the impact of golden moles (Amblysomus sp.) on the abundance, diversity, and community structure of nematodes in kweek grass (Cynodon dactylon) within the Sovenga Hills of Limpopo Province, South Africa. Eight sites were sampled: four with active moles (sites: M1–M4), and four without (sites: T1–T4). Eighty soil samples were collected, and nematodes were extracted. A total of 23 nematode genera were identified, including 3 plant-parasitic and 20 free-living genera. The frequency of occurrence (FO) data showed that Aphelenchus sp. and Acrobeles sp. were the most prevalent nematodes, each occurring in 87.5% of the samples. In contrast, Eucephalobus sp., Tripylina sp., Discolaimus sp., and Tylenchus sp. had the lowest FO, appearing in only 12.5% of samples. The diversity indices (the Shannon index, the maturity index, and the plant-parasitic index) showed significant differences between the two environments. The Shannon index (H′) and maturity index were the most effective indicators of ecosystem disturbance. The lowest H′ was found at T4 (1.7 ± 0.2), compared with a higher value at M1 (2.4 ± 0.1). The principal component analysis (PCA) results revealed a positive correlation between Ditylenchus and the clay in the soil. In addition, Cervidellus was associated with soil pH. Network analysis revealed increased complexity in the nematode community structure at mole-affected sites. These findings suggest that mole activity alters soil properties and indirectly affects nematode diversity and trophic structure. Full article

Precisely recognizing diseases in tomato leaves plays a crucial role in enhancing the health, productivity, and quality of tomato crops. However, disease identification methods that rely on single-mode information often face the problems of insufficient accuracy and weak generalization ability. Therefore, this paper proposes a tomato leaf disease recognition framework FCMNet based on multimodal fusion, which combines tomato leaf disease image and text description to enhance the ability to capture disease characteristics. In this paper, the Fourier-guided Attention Mechanism (FGAM) is designed, which systematically embeds the Fourier frequency-domain information into the spatial-channel attention structure for the first time, enhances the stability and noise resistance of feature expression through spectral transform, and realizes more accurate lesion location by means of multi-scale fusion of local and global features. In order to realize the deep semantic interaction between image and text modality, a Cross Vision–Language Alignment module (CVLA) is further proposed. This module generates visual representations compatible with Bert embeddings by utilizing block segmentation and feature mapping techniques. Additionally, it incorporates a probability-based weighting mechanism to achieve enhanced multimodal fusion, significantly strengthening the model’s comprehension of semantic relationships across different modalities. Furthermore, to enhance both training efficiency and parameter optimization capabilities of the model, we introduce a Multi-strategy Improved Coati Optimization Algorithm (MSCOA). This algorithm integrates Good Point Set initialization with a Golden Sine search strategy, thereby boosting global exploration, accelerating convergence, and effectively preventing entrapment in local optima. Consequently, it exhibits robust adaptability and stable performance within high-dimensional search spaces. The experimental results show that the FCMNet model has increased the accuracy and precision by 2.61% and 2.85%, respectively, compared with the baseline model on the self-built dataset of tomato leaf diseases, and the recall and F1 score have increased by 3.03% and 3.06%, respectively, which is significantly superior to the existing methods. This research provides a new solution for the identification of tomato leaf diseases and has broad potential for agricultural applications. Full article

Bacteriophages (phages), the most abundant biological entities on Earth, have long served as both model systems and therapeutic tools. Recent advances in synthetic biology and genetic engineering have revolutionized the capacity to tailor phages with enhanced functionality beyond their natural capabilities. This review outlines the current landscape of synthetic and functional engineering of phages, encompassing both in-vivo and in-vitro strategies. We describe in-vivo approaches such as phage recombineering systems, CRISPR-Cas-assisted editing, and bacterial retron-based methods, as well as synthetic assembly platforms including yeast-based artificial chromosomes, Gibson, Golden Gate, and iPac assemblies. In addition, we explore in-vitro rebooting using TXTL (transcription–translation) systems, which offer a flexible alternative to cell-based rebooting but are less effective for large genomes or structurally complex phages. Special focus is given to the design of customized phages for targeted applications, including host range expansion via receptor-binding protein modifications, delivery of antimicrobial proteins or CRISPR payloads, and the construction of biocontained, non-replicative capsid systems for safe clinical use. Through illustrative examples, we highlight how these technologies enable the transformation of phages into programmable bactericidal agents, precision diagnostic tools, and drug delivery vehicles. Together, these advances establish a powerful foundation for next-generation antimicrobial platforms and synthetic microbiology. Full article

The main objective of this paper is to investigate the properties related to the sectional curvatures of a Kähler golden manifold, an almost Hermitian golden manifold whose almost complex golden structure is parallel with respect to the Levi–Civita connection. Under certain conditions, we prove that a Kähler golden manifold with constant sectional curvature is flat. We introduce the concepts of $\Phi$-holomorphic sectional curvature and $\Phi$-holomorphic bi-sectional curvature on a Kähler golden manifold, and compare them respectively with the holomorphic sectional curvature and holomorphic bi-sectional curvature on a Kähler manifold. Full article