Search Results (55)

Canolol is a pivotal phenolic antioxidant in rapeseed oil, yet its specific antioxidant mechanism and stability determinants during storage remain poorly understood. This study elucidates the antioxidant pathway of canolol within a lipid autoxidation model and evaluates its stability during the 52-week storage (25 ± 2 °C) of microwave-pretreated rapeseeds under varying packaging conditions. Rapeseeds were packaged in polyamide/polyethylene (PA/PE) vacuum bags and polypropylene (PP) atmospheric bags, and then monitored for seed quality, oil oxidative indices, and micronutrient contents. Via high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (HPLC-Q-TOF/MS/MS), a canolol-derived dimeric oxidation product (C₂₀H₂₄O₇, m/z 375.1437) was tentatively identified in an 2,2’-azobis(isobutyronitrile) (AIBN)-initiated ethyl linoleate (EtL) autoxidation system. The MS/MS fragmentation pattern—characterized by neutral H₂O loss, sequential •CH₃ eliminations, and syringyl-type diagnostic ions—supports a mechanism involving hydrogen atom transfer (HAT) from canolol to lipid-derived peroxyl radicals. This is followed by the oxidative cross-coupling of a canolol-derived phenoxyl radical (ArO•) with a hydroxyethylated intermediate (Ar′O•), confirming canolol’s role as a chain-breaking antioxidant. Correlation analyses confirmed canolol as the primary antioxidant (r = −0.914, −0.984/−0.959, −0.883 with acid value/peroxide value, p < 0.01), with a synergistic effect relationship with tocopherols (r = 0.878, 0.966, p < 0.01). PA/PE vacuum packaging (low oxygen permeability) significantly mitigated canolol degradation (22.41% loss vs. 76.34% in PP), reducing tocopherol loss and oil oxidation. This study clarifies canolol’s antioxidant pathway in rapeseed oil, providing theoretical insights for phenolic antioxidant research and practical packaging guidance for the edible oil industry. Full article

We designed a supervised machine learning framework to predict standard Gibbs free energies, ΔG°, of formal hydrogen atom transfer (f-HAT) for phenolic antioxidants across different radicals and media, enabling rapid and chemically interpretable screening. We curated a DFT dataset of 71 molecules (phenolic compounds and anthocyanidins), with 207 reaction sites, 10 radical reactive oxygen/sulfur species, and three environments (leading to a total of 6210 ΔG° values). The models amass 106 numerical RDKit descriptors, augmented with one-hot encodings of medium, site, radical, and structural class, and were evaluated through a leave-one-molecule-out protocol. Among the tested regression algorithms, the random forest regressor provides the best balance of accuracy and robustness with both R² test (≈0.94) and MAE (2.74 kcal mol⁻¹; RMSE (≈5.0 kcal mol⁻¹)), close to DFT chemical accuracy. The feature-importance analysis revealed that “electronic” and “experimental” (site/group) descriptors primarily drive predictions, with the radical’s maximum absolute partial charge being the most important descriptor in the prediction of a radical’s ΔG°. These results suggest that descriptor-driven RF (Random Forest) models can generalize across chemical space to provide interpretable ΔG° predictions, providing a path for chemists towards a scalable route to prioritize antioxidant candidates for broader molecular families. Full article

Background/Objectives: Electronic cigarettes (e-cigarettes) are an important public health concern, particularly amongst young individuals. This study aimed to assess the attitudes and factors, including mental distress, that influence e-cigarette use amongst university students in Southern Thailand, including in armed conflict areas. Methods: A cross-sectional survey was conducted at the Prince of Songkla University across two campuses: Hat yai and Pattani. Data on demographics, attitudes towards e-cigarettes, usage patterns, and mental health (using the 21-item Depression, Anxiety, and Stress Scale) were collected and analysed using R software. Results: Amongst 901 participants (236 men and 665 women), the prevalence of e-cigarette use was 6.9%. Men (OR = 2.65; 95% CI = [1.28, 5.46]), tobacco users (OR = 97.56; 95% CI = [26.77, 355.66]), and those living alone (OR = 13.48; 95% CI = [1.21, 150.47]) were more likely to engage in e-cigarette use. Additionally, Islamic students reported lower usage rates than their Buddhist counterparts (OR = 0.32; 95% CI = [0.11, 0.9]). Conclusions: E-cigarette users exhibited higher scores on the depression, anxiety, and stress subscales than non-users. Smokers perceived e-cigarettes as a means of reducing tobacco consumption, alleviating stress, and enhancing their image. Moreover, non-smokers believed that e-cigarettes should be ‘illegal’ in Thailand. Full article

Liquid metal embrittlement (LME) during hot stamping of Zn-coated high-strength steels poses significant challenges to the long-term durability of automotive components. This study investigates how ~30 μm deep LME cracks affect the mechanical behavior of Zn-coated high-strength boron steel. LME-free flat specimens were compared with hat-shaped specimens containing LME cracks. While tensile strength and ductility exhibited minimal changes, the high-cycle fatigue limit (R = −1, 10⁷ cycles) decreased by 10.9% from 550 MPa to 490 MPa in hat-shaped specimens. Fractographic examination revealed distinct stress-dependent crack initiation mechanisms: at high stress amplitudes (≥690 MPa), LME cracks competed with intrinsic substrate defects but did not dominate fatigue failure. In contrast, at moderate-to-low stress amplitudes (≤630 MPa), LME cracks dominated fatigue degradation through a multi-site crack initiation tendency. El Haddad analysis positioned these cracks at the short-to-long crack transition boundary (l ≈ l₀). Preliminary fracture mechanics analysis reveals that conventional single-crack LEFM models systematically overestimate the fatigue threshold stress for LME-affected specimens, a discrepancy qualitatively attributed to the high surface density and morphological complexity of LME crack networks and to chemically assisted grain boundary weakening induced by liquid Zn infiltration—effects not captured by standard fracture mechanics frameworks. These results establish the stress-dependent mechanisms governing LME crack-induced fatigue degradation and provide a mechanistic basis for the development of more accurate fatigue life prediction methods for Zn-coated hot-stamped high-strength steels. Full article

Gross primary production (GPP) is a key indicator to evaluating ecosystem carbon sinks. Southwest China is characterised by diverse ecosystems and abundant forest resources and represents one of the most important carbon reservoirs in China. Therefore, a quantitative assessment of the uncertainty of existing GPP products and their influencing factors is important. This study investigates GPP uncertainties and its influencing factors based on the three-cornered hat (TCH) and XGBoost and SHAP methods. Thirteen products were examined, including six products from the light use efficiency (LUE) model, two products from the process-based (Process) model, three products from the machine learning (ML) model and two products from satellite-based direct proxies (Proxies). The results reveal the following: (1) All products show similar spatial patterns, with Process products fluctuating notably in 2010, 2011, and 2014, while others remain stable. (2) Relative uncertainty is lowest annually, increasing monthly and daily; ML products exhibit greater stability. Among them, CEDAR has the least uncertainty and strongest agreement with flux observations (r = 0.82), whereas EC-LUE shows the highest uncertainty. (3) Vegetation index, elevation and radiation are more influential than other factors. These findings aid GPP product selection and uncertainty assessment in complex terrains with sparse ground data. Full article

Panax notoginseng, a high-value medicinal crop, suffers substantial yield losses due to Fusarium oxysporum-mediated root rot, for which no molecularly defined control targets are currently available. Histone acetyltransferases (HATs) serve as crucial epigenetic regulators of fungal development and stress responses; however, their functional roles in F. oxysporum remain largely unexplored. In this study, we systematically identified six FoHAT genes via genome-wide analysis and classified them into evolutionarily conserved subfamilies through phylogenetic comparison with orthologs from Saccharomyces cerevisiae, Homo sapiens, and Arabidopsis thaliana. Structural analyses revealed distinct motif compositions and domain architectures among FoHAT members, while promoter cis-element profiling suggested potential subfunctionalization via stress-responsive regulatory mechanisms. Functional investigations demonstrated that major notoginsenosides present in P. notoginseng root exudates—R₁, Rg₁, Rg₂, Re, and Rd—dynamically influenced both spore germination and FoHAT expression profiles. Intriguingly, each notoginsenoside exerted concentration-dependent non-linear effects on spore germination, either inhibiting or promoting the process. Concurrently, notoginsenoside exposure triggered compensatory transcriptional responses, most notably a rebound in Fo-Hat1_N expression from 9% to 112% under Rd treatment. This work establishes an initial epigenetic framework for combating Fusarium root rot in medicinal plants and offers a foundation for developing HAT-targeted small-molecule inhibitors. Full article

Three free-living marine nematode species of the family Desmodoridae are described and illustrated based on light and scanning electron microscopy. Pseudochromadora paraparva sp. nov. was collected from muddy sand sediments at Eulwangri Beach, Incheon, Korea, and P. capitata sp. nov. from sublittoral muddy sediments off Jindo Island, Korea. Metachromadora itoi Kito, 1978, is also recorded for the first time from Korean waters, based on specimens from sandy sediments off Jeju Island. Pseudochromadora paraparva sp. nov. is distinguished from P. parva Gagarin & Thanh, 2008 and related congeners by having a tripartite cephalic region consisting of a jar-shaped main capsule, an anterior transition zone with weaker cuticle bearing the cephalic setae, and a highly elevated hat-shaped labial region. It additionally shows a sexually dimorphic amphideal fovea, a unique arrangement of precloacal thorns, a gubernaculum with a dorsal apophysis, and ventral thorns lacking cuticular hillocks. Pseudochromadora capitata sp. nov. is characterized by a cephalic region composed of a rounded labial region and a thickly cuticularized main capsule, together with a sexually dimorphic amphideal fovea, arcuate spicules with a large hammer-shaped capitulum, a gubernaculum with a dorsal apophysis, and 3–8 precloacal and 3–5 postcloacal thorns arranged in a row. Molecular data (18S and 28S rRNA) were generated for both new species, and phylogenetic analyses support their placement within the genus Pseudochromadora and provide molecular evidence distinguishing them from closely related congeners. Scanning Electron Microscope (SEM) observations of M. itoi also revealed multiple configurations of the buccal cavity, providing additional morphological information useful for understanding structural variation within the genus. These findings refine the taxonomic framework within the Desmodoridae and expand current knowledge of morphological diversity in free-living marine nematodes. Full article

In psychology, small sample sizes are a frequent challenge—particularly when studying specific expert populations or using complex and cost-intensive methods like human scoring of creative answers—as they reduce statistical power, bias results, and limit generalizability. They also hinder the use of frequentist confirmatory factor analysis (CFA), which depends on larger samples for reliable estimation. Problems such as non-convergence, inadmissible parameters, and poor model fit are more likely. In contrast, Bayesian methods offer a robust alternative, being less sensitive to sample size and allowing the integration of prior knowledge through parameter priors. In the present study, we introduce small-sample-size structural equation modeling to creativity research by investigating the relationship between creative fluency and nested creative cleverness with right-wing authoritarianism, starting with a sample size of N = 198. We compare the stability of results in frequentist and Bayesian SEM while gradually reducing the sample by n = 25. We find that common frequentist fit indexes degrade below N = 100, while Bayesian multivariate Rhat values indicate stable convergence down to N = 50. Standard errors for fluency loadings inflate 40–50% faster in frequentist SEM compared to Bayesian estimation, and regression coefficients linking RWA to cleverness remain significant across all reductions. Based on these findings, we discuss (1) the critical role of Bayesian priors in stabilizing small-sample SEM, (2) the robustness of the RWA-cleverness relationship despite sample constraints, and (3) practical guidelines for minimum sample sizes in bifactor modeling. Full article

During a survey of the west coast of South Korea, two new Pseudochromadora species were recorded from Yeongjongdo Island. Descriptions of two new species, an updated list of valid species within the genus, a tabular key, partial sequences of mtCOI, near full-length SSU, and the D2–D3 region of LSU rDNA, together with phylogenetic analyses are provided. The two new species are classified as Pseudochromadora based on having a two-portioned cephalic capsule, unispiral amphidial fovea, lateral alae extending from the posterior end of the pharynx as far as the tail, and presence of copulatory thorns, as well as a short conical tail. The two species are distinguished from each other by their different types of labial regions of the cephalic capsule (round-shaped vs. hat-shaped). The two species, despite being found in the same locality, are morphologically and molecularly distinct from one another. Pairwise Kimura 2-parameter (K2P) distances between the two new species were 10.6% (18S) and 27.2% (28S), values consistent with interspecific divergence observed among congeners. Phylogenetic analyses showed both species as distinct lineages within Pseudochromadora. In the 28S rDNA tree, each was retrieved as a well-supported monophyletic clade with congeners, whereas in the 18S tree, all congeners including the two new species formed a single clade, except for P. plurichela, which branched outside the main group. These results highlight potential paraphyly within Pseudochromadora and suggest that overlooked morphological traits may hold phylogenetic significance, warranting further investigation. Full article

Hydrogen atom transfer (HAT) is a fundamental class of radical transformations that enables the direct generation of open-shell radical intermediates from R–H bonds (R = C, N, etc.), offering unique opportunities for green and sustainable synthesis. Significant progress has been made not only in identifying diverse molecular scaffolds capable of mediating HAT but also in developing synthetic methodologies to achieve precise stereocontrol in these processes. In this context, this review highlights recent advances in the use of sugar-derived compounds, cysteine-containing peptides, and chiral/achiral thiols/thiophenols as catalysts for stereoselective HAT, emphasizing their potential to expand the synthetic utility of HAT in organic transformations. Full article

African trypanosomiasis is a protozoan disease that affects both humans and animals. Human African Trypanosomiasis (HAT) is a Neglected Tropical Disease targeted for elimination in 2030. Although WHO has not reported HAT from Nigeria in the last decade, there are published studies reporting seroprevalence, parasite detection/isolation, and animal reservoirs potentially involved in HAT transmission in Nigeria. Interestingly, the burden of Animal African Trypanosomiasis (AAT) continues to increase. In this study, we synthesized published reports on the prevalence of HAT and AAT in Nigeria from 1993–2021, the trypanosome species involved, the spread of animal reservoirs, and the variability in diagnostic methodologies employed. A scoping review was performed following the methodological framework outlined in PRISMA-ScR checklist. Sixteen eligible studies published between 1993 and 2021 were reviewed: 13 for AAT and 3 for HAT. Varying prevalence rates were recorded depending on the diagnostic methods employed. The average prevalence reported from these studies was 3.3% (HAT), and 27.3% (AAT). Diagnostic methods employed include microscopy, PCR and Card Agglutination Test for Trypanosomiasis (CATT). Cattle, pigs, and dogs were identified as carriers of human-infective trypanosomes. This study highlights the scarcity of HAT epidemiological studies/data from Nigeria, the high prevalence, complex epidemiology, limited attention and surveillance of African Trypanosomiasis in Nigeria. Remarkably, WHO records do not reflect the published data showing evidence of HAT prevalence/cases in Nigeria. Unfortunately, diagnostics challenges and unrealistic disease reporting protocols seem to limit HAT reporting from Nigeria. Therefore, adequately coordinated epidemiological surveys and targeted intervention policies are imperative to ascertain the true epidemiological status of HAT in Nigeria and prevent disease re-emergence towards achieving WHO’s elimination targets. The presence of animal carriers of human-infective trypanosomes underscores the importance of a one-health approach to combat African trypanosomiasis effectively. Full article

In this research work, we proposed and studied a fractional-order model for Human African Trypanosomiasis (HAT) disease transmission, incorporating three control strategies: health education campaigns, prevention measures, and use of insecticides. The theoretical analysis of the model was presented, including the computation of disease-free equilibrium and basic reproduction number. We performed the stability analysis of the model and the results showed that the disease-free equilibrium point was locally asymptotically stable whenever ${\mathcal{R}}_0<1$ and unstable when ${\mathcal{R}}_0>1$. Furthermore, we performed parameter estimation of the model using HAT-reported cases in Tanzania. The results showed that fractional-order model had a better fit to the real data compared to the classical integer-order model. Sensitivity analysis of the basic reproduction number was performed using computed partial rank correlation coefficients to assess the effects of parameters on HAT transmission. Additionally, we performed numerical simulations of the model to assess the impact of memory effects on the spread of HAT. Overall, we observed that the order of derivatives significantly influences the dynamics of HAT transmission in the population. Moreover, we simulated the model to assess the effectiveness of proposed control strategies. We observed that the use of insecticides and prevention measures have the potential to significantly reduce the spread of HAT within the population. Full article

Accurate quantification of evapotranspiration (ET) is crucial for agricultural water management and climate change adaptation, especially in global warming and extreme climate events. Despite the availability of various ET products, their applicability across different scales and climatic conditions has not been comprehensively verified. This study evaluates nine ET products at grid, basin, and site scales in China from 2003 to 2014 under varying climatic conditions, including extreme temperatures, vapor pressure deficit (VPD), and drought. The main results are as follows: (1) At the grid scale, all products except the MODIS/Terra Net Evapotranspiration 8-Day L4 Global 500m SIN Grid (MOD16A2) product showed high consistency, with the Global Land Evaporation Amsterdam Model V4.2a (GLEAM) product exhibiting the highest comparability. The three-cornered hat (TCH) method revealed that GLEAM and the Synthesized Global Actual Evapotranspiration Dataset (Syn) had low uncertainties in multiple basins, while the Reliability Ensemble Averaging (REA) product and Penman–Monteith–Leuning Evapotranspiration V2 (PMLv2) product had the smallest uncertainties in the Songhua River and Hai River Basins. (2) At the basin scale, ET products were closely aligned with water-balance-based ET (WB-ET), with GLEAM achieving the smallest root mean square error (RMSE) (22.94 mm/month). (3) At the site scale, accuracy decreased significantly under extreme climatic conditions, with the coefficient of determination (R²) dropping from about 0.60 to below 0.30 and the mean absolute error (MAE) increasing by 110.30% (extreme high temperatures) and 101.40% (extreme high VPD). Drought conditions caused slight instability in ET estimations, with MAE increasing by approximately 12.00–40.00%. (4) Finally, using a small number of daily ET products as inputs for machine learning models, such as random forest (RF), greatly improved ET estimation, with R² reaching 0.91 overall and 0.81 under extreme conditions. GLEAM was the most important product for RF in ET estimation. This study provides essential guidance for selecting and improving ET products to enhance agricultural water-use efficiency and sustainable irrigation. Full article

Eurasian drylands are vital for the global climate and ecological balance. Quantifying spatiotemporal variations in surface soil moisture (SSM) is essential for monitoring water, energy, and carbon cycles. The suitability of recent global-scale surface soil moisture datasets for Eurasian arid and semi-arid regions has not been comprehensively evaluated. This study investigates spatiotemporal trends of five SSM products—MERRA-2, ESACCI, GLEAM, GLDAS, and ERA5—from 1980 to 2023. The performance of these products was evaluated using in situ station data and the three-cornered hat (TCH) method, followed by partial correlation analysis to assess the influence of environmental factors, including mean annual temperature (MAT), mean annual precipitation (MAP), potential evapotranspiration (PET), vapor pressure deficit (VPD), and leaf area index (LAI), on SSM from 1981 to 2018. The results showed consistent SSM patterns: higher values in India, the North China Plain, and Russia, and lower values in the Arabian Peninsula, the Iranian Plateau, and Central Asia. Regionally, MAT, PET, VPD, and LAI increased significantly (0.04 °C yr⁻¹, 1.66 mm yr⁻¹, 0.004 kPa yr⁻¹, and 0.003 m² m⁻² yr⁻¹, respectively; p < 0.05), while MAP rose non-significantly (0.29 mm yr⁻¹). ERA5 exhibited the strongest correlation with in situ station data (R² = 0.42), followed by GLEAM (0.37), ESACCI (0.28), MERRA2 (0.19), and GLDAS (0.17). Additionally, ERA5 showed the highest correlation (correlation = 0.72), while GLEAM had the lowest bias (0.03 m³ m⁻³) and ESACCI exhibited the lowest ubRMSE (0.03 m³ m⁻³). The three-cornered hat method identified ERA5 and GLDAS as having the lowest uncertainties (<0.03 m³ m⁻³), with ESACCI exceeding 0.05 m³ m⁻³ in northern regions. Across land cover types, cropland had the lowest uncertainty among the five SSM products, while forest had the highest. Partial correlation and dominant factor analysis identified MAP as the primary driver of SSM. This study comprehensively evaluated SSM products, highlighting their strengths and limitations. It underscored MAP’s crucial role in SSM dynamics and provided insights for improving SSM datasets and water resource management in drylands, with broader implications for understanding the hydrological impacts of climate change. Full article

Rebar constitutes a crucial element within tunnel lining structures, where its precise arrangement plays a pivotal role in determining both structural stability and load-bearing capacity. Due to the rebar’s high dielectric constant approaching infinity, radar signal reflections are intensified, manifesting as distinct hyperbolic patterns within radar imagery. By performing convolutional operations, these hyperbolic features of rebar can be effectively extracted from radar images. Building upon the feature extraction capabilities of the ResNet50 model, this study introduces a Deformable Attention to Capture Salient Information (DAS) mechanism, employing deformable and separable convolutions to enhance rebar localization and concentrate on hyperbolic features resulting from multiple reflections. Before the Region Proposal Network (RPN) and region of interest (ROI) pooling stages in Faster R-CNN, this study integrates a hyperbolic attention (HAT) module. Through refined distance metrics, the hyperbolic attention mechanism enhances the network’s Precision in identifying rebar hyperbolic features within feature maps. To ensure robustness across diverse conditions, this study utilizes a simulated public dataset for tunnel linings, alongside real data from the Husa Tunnel, to create a comprehensive ground-penetrating radar image dataset for tunnel linings. Experimental results indicate that the proposed model achieved an Average Precision of 94.93%, reflecting a 3.14% increase compared to the baseline model. Lastly, in a random selection of 50 radar images for testing, the model achieved a rebar detection accuracy of 93.46%, representing an enhancement of 0.94% over the baseline model. Full article