Browse Articles

Research on the bearing performance of HSCA high-strength preloaded expansion piles in calcareous sand foundation

Diversity and composition of vegetation and soil seed banks after sand dune restoration by oil mulching and plantations

Abstract Soil seed bank (SSB) is valuable reserves of seeds hidden in the soil and are especially important for the preservation and establishment of vegetation under adverse environmental conditions. However, there is a lack of knowledge on the effects of restoration measures on SSB, especially in arid ecosystems. Here, we assess the impacts of oil mulching (1 and 3 years after mulching) and plantations (15-year-old) on the diversity and composition of SSB and aboveground vegetation (AGV) in comparison with those in non-restored areas (i.e., control). Based on the results, species richness was poor in the studied area (36 species belonging to 16 families), with a lower contribution of SSB than of AGV (11 and 34 species, respectively). The largest number of exclusive species was observed in the planted treatment for both SSB and AGV (4 and 5 species, respectively), while the lowest was found in the 1-yr mulching treatment. The mean comparison of the diversity indices revealed that the highest values occurred in the plantation and 3-yr-mulching plots. The seed density in the plantation area was significantly greater (4145 ± 694 seeds/m2) than that in the other areas (3-yr-mulching > 1-yr-mulching > control treatments (145 ± 53, 65 ± 28, and 43 ± 22, respectively). The results of the DCA showed that the plantation treatment was completely separated from the other treatments in terms of the plant composition of the AGV, and the treatment closest to that area was 3-yr mulching, which indicates the positive effect of time since mulching on plant composition. The results of this study suggest that there is a trade-off between the short-term and medium-term effects of oil mulching, such that in the early years, oil mulching has a negative effect on the AGV and SSB, but its positive effects increase with time since mulching. It can be concluded that mulching, along with afforestation, creates a favorable microclimate and improves the diversity and composition of AGV and SSB.

Development of detection system for lead ions in mixture solutions using UV-Vis measurements with peptide immobilized microbeads

Comprehensive pan-cancer analysis reveals NTN1 as an immune infiltrate risk factor and its potential prognostic value in SKCM

Cardiovascular disease risk in Korean patients with systemic lupus erythematosus compared to diabetes mellitus and the general population

Fluid flow impacts endothelial-monocyte interactions in a model of vascular inflammatory fibrosis

Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach

Rubber intercropping with arboreal and herbaceous species alleviated the global warming potential through the reduction of soil greenhouse gas emissions

Health literacy and influencing factors in university students across diverse educational fields in Kazakhstan

Pseudogenization of the Slc23a4 gene is necessary for the survival of Xdh-deficient mice

Characteristics of transition to turbulence in a healthy thoracic aorta using large eddy simulation

Machine Learning-Based predictive model for adolescent metabolic syndrome: Utilizing data from NHANES 2007–2016

Abstract Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hypertension, and insulin resistance, increasing risks of cardiovascular disease and mental health problems. Early detection and intervention are crucial but often hindered by complex diagnostic requirements. This study aims to develop a predictive model using NHANES data, excluding biochemical indicators, to provide a simple, cost-effective tool for large-scale, non-medical screening and early prevention of adolescent MetS. After excluding adolescents with missing diagnostic variables, the dataset included 2,459 adolescents via NHANES data from 2007–2016. We used LASSO regression and 20-fold cross-validation to screen for the variables with the greatest predictive value. The dataset was divided into training and validation sets in a 7:3 ratio, and SMOTE was used to expand the training set with a ratio of 1:1. Based on the training set, we built eight machine learning models and a multifactor logistic regression model, evaluating nine predictive models in total. After evaluating all models using the confusion matrix, calibration curves and decision curves, the LGB model had the best predictive performance, with an AUC of 0.969, a Youden index of 0.923, accuracy of 0.978, F1 score of 0.989, and Kappa value of 0.800. We further interpreted the LGB model using SHAP, the SHAP hive plot showed that the predictor variables were, in descending order of importance, BMI age sex-specific percentage, weight, upper arm circumference, thigh length, and race. Finally, we deployed it online for broader accessibility. The predictive models we developed and validated demonstrated high performance, making them suitable for large-scale, non-medical primary screening and early warning of adolescent Metabolic syndrome. The online deployment of the model allows for practical use in community and school settings, promoting early intervention and public health improvement.

A cross-tissue transcriptome-wide association study identifies new susceptibility genes for benign prostatic hyperplasia

Branched-chain amino acids and specific phosphatidylinositols are plasma metabolite pairs associated with menstrual pain severity

Controlling the energies of the single-rotor large wind turbine system using a new controller

Personality traits of women with hereditary risk for breast/ovarian cancer versus obstetric history and cancer preventive behaviors

Abstract The aim of the study is to analyze the relationship between personality traits of women with hereditary predisposition to breast/ovarian cancer and their obstetric history and cancer-preventive behaviors. A total of 357 women, participants of ‘The National Program for Families With Genetic/Familial High Risk for Cancer’, were included in the study. The Neo Five-Factor Inventory (NEO-FFI) and a standardized original questionnaire designed for the purpose of the study were used. Breast ultrasound examination at a younger age was associated with Extraversion. Openness to Experience was linked with lower number of children, more frequent use of hormonal contraceptives, and younger age at first breast ultrasound examination. Women with higher Agreeableness scores were less likely to use contraceptives and underwent their first breast ultrasound later in life. Conscientiousness was associated with more frequent use of hormonal contraceptives and younger age at first breast ultrasound examination. Women at increased risk for developing breast/ovarian cancer who used hormonal contraceptives underwent breast ultrasound examinations earlier in life, while those who had breastfed their children chose to have their first mammogram earlier in life. Personality traits affect health-related behaviors and should be taken into account when designing theoretical models as well as interventions regarding health habits.

Protective effect of Panax ginseng extract on cisplatin-induced AKI via downregulating cell death associated genes

Unveiling the omics tapestry of B-acute lymphoblastic leukemia: bridging genomics, metabolomics, and immunomics

Imaging cells and nanoparticles using modulated optically computed phase microscopy

$$\hbox {H}_2$$-roaming dynamics in the formation of $$\hbox {H}_{3}^{+}$$ following two-photon double ionization of ethanol and aminoethanol

Abstract Roaming reactions involving a neutral fragment of a molecule that transiently wanders around another fragment before forming a new bond are intriguing and peculiar pathways for molecular rearrangement. Such reactions can occur for example upon double ionization of small organic molecules, and have recently sparked much scientific interest. We have studied the dynamics of the $$\hbox {H}_2$$ -roaming reaction leading to the formation of $$\hbox {H}_3^+$$ after two-photon double ionization of ethanol and 2-aminoethanol, using an XUV-UV pump-probe scheme. For ethanol, we find dynamics similar to previous studies employing different pump-probe schemes, indicating the independence of the observed dynamics from the method of ionization and the photon energy of the disruptive probe pulse. Surprisingly, we do not observe a kinetic isotope effect in ethanol- $$\hbox {D}_6$$ , in contrast to previous experiments on methanol where such an effect was observed. This distinction indicates fundamental differences in the energetics of the reaction pathways as compared to the methanol molecule. The larger number of possible roaming pathways compared to methanol complicates the analysis considerably. In contrast to previous studies, we additionally analyze a broad range of dissociative ionization products, which feature distinct dynamics from that of $$\hbox {H}_{3}^{+}$$ and allow initial insight into the action of the disruptive UV-probe pulse.