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Pinwheel blowing and stress ball squeezing reduce children’s pain and anxiety during intravenous catheterization in a randomized controlled trial
Optimal selection of SiC and TiO2 reinforced ZA27 hybrid nanocomposite exercising PSI approach under fuzzy environment for bearing application
Leader prohibitive voice shapes employee voice through psychological safety moderated by self-efficacy and generational differences
Behavior of unsaturated sandy loess under high-frequency unilateral cyclic loading
Abstract Sandy loess, which is distinguished by its granular composition dominated by sand particles and minimal clay, is vulnerable to structural destabilization under cyclic loading. This report focuses on recurrent geotechnical failures in the hydrocarbon extraction zones of China’s Loess Plateau. The investigation employs cyclic triaxial testing to evaluate the moisture-dependent and frequency-governed mechanical behaviors of unsaturated sandy loess, particularly in the context of the Maliancheng Village landslide event. Beyond the plastic limit threshold, the moisture content has negligible effects on the stress–strain hysteresis, shear rigidity, and energy dissipation of the system. However, sub-plastic-limit conditions induce strain amplification by increasing damping ratios and decreasing shear resistance. Meanwhile, the strain magnitude and shear stiffness increase proportionally with loading frequency, whereas damping responses have an inverse frequency relationship. Notably, high-rate cyclic loads have less of an influence on early-phase mechanical signatures. Progressive strain accumulation under sustained high-frequency loading follows triphasic evolution, i.e., exponential escalation, transitional refinement, and metastable equilibrium, while stabilization cycles escalate nonlinearly as a function of the applied stress.
Targeted and safe delivery of colchicine via polymeric nanocarriers for potential atherosclerosis therapy with in vitro and in vivo evaluation
Predicting regional and temporal incidence of RSV and influenza hospitalizations in a birth cohort of young Australian children
Peculiarities in thermal transport of nanostructured silicon arrays with different morphology
Abstract This study explores the thermal conductivity of nanostructured porous silicon with different morphology produced by metal-assisted chemical etching of silicon wafers with different dopants, doping levels and crystallographic orientation. The wide range of morphological structures observed in the samples strongly depends on the initial wafer characteristics, a factor that cannot be neglected. While previous studies have demonstrated the qualitative capabilities of photoacoustic and Raman spectroscopy in characterizing nanostructured silicon, our work highlights the quantitative discrepancies that can arise when combining these techniques to investigate thermal properties. The differences in the results obtained using these methods can be attributed to the distinct nature of the information they provide: photoacoustic spectroscopy probes the effective thermal conductivity over larger areas, whereas Raman spectroscopy offers localized measurements. Furthermore, our Monte Carlo simulations provide insights into the morphological features of porous silicon that influence the interpretation of experimental data. This study underscores the importance of a comprehensive approach, combining both experimental and theoretical methods, to accurately assess the thermal transport properties of nanostructured materials.
Worked human bones and the rise of urban society in the neolithic Liangzhu culture, East Asia
Enhancing thermal performance of phase change materials using conductive rods with length dependent melting dynamics
Abstract Phase change materials (PCMs) suffer from slow melting rates due to their low thermal conductivity, limiting their efficiency in thermal energy storage systems. This study numerically investigates the novel use of copper rods as conductive enhancers to accelerate PCM melting in a horizontally placed hemispherical cell. Using the ANSYS/FLUENT 16 with an enthalpy-porosity model, the impact of rod integration is examined to determine the optimal rod configuration for maximising heat transfer while minimising melting time. The results indicate that copper rods dramatically improved melting performance: a 20 mm rod can reduce total melting time by 70% (from 300 to 90 min), while 10 mm and 15 mm rods achieve reductions of 40% (to 180 min) and 50% (to 150 min), respectively. Clearly, the 20 mm rod enables 70% liquid fraction in 30 min, showing a melting speed four times faster than the no-rod case. Nonlinear scaling reveals diminishing returns beyond 15 mm, suggesting a cost-performance trade-off at this length. The 15 mm rod emerged as a practical balance between attaining 85% of maximum gain with a 50% reduction in melting time while utilising 25% less copper than 20 mm rod. Accordingly, this research provides critical insights for designing high-efficiency thermal storage systems, offering a roadmap to optimise conductive enhancements for real-world applications. By bridging the gap between material properties and system-level performance, the findings advance the deployment of PCMs in renewable energy and waste heat recovery systems.
Mechanism and control technology of roadway floor heave deformation and failure under the influence of repeated mining in multiple coal seams
Abstract Deformations caused by of roadway floor heave due to the repeated mining of multiple coal seams is a prominent problem in deep coal mining. This work examines roadway floor heave under the influence of repeated mining in multiple coal seams as the research object. Through theoretical analysis, numerical simulation, and field experiments, the failure mechanism of floor heave deformation is revealed, and effective control techniques are proposed. A deformation model for multiple-seam repeated mining was established based on the theory of elastic mechanics, and a control mechanism was analysed. An optimised treatment method for roadway floor heave was proposed. Displacement, stress, and failure zone analyses of the original support and optimised surrounding rock were conducted via FLAC3D software, and the optimal treatment method for roadway floor heave was obtained. The applicability of this support method was verified through onsite application. The results indicate that stress superposition is the cause attributed to the repeated mining of multiple coal seams, and stress reduction and effective roof support are the keys to preventing and controlling roadway floor heave. Compared with the original support method, the amount of floor heave was reduced by 60%, and the shrinkage of the two sides was also significantly reduced. The optimised roadway support method provides better control over floor heave.
Artificial intelligence-assisted quality control circles led by clinical pharmacists to improve the rational use of parenteral proton pump inhibitors among hospitalised patients
Investigating toxicity and Bias in stable diffusion text-to-image models
Abstract Text-to-image models are increasingly popular and impactful, yet concerns regarding their safety and fairness remain. This study investigates the ability of ten popular Stable Diffusion models to generate harmful images, including sexual, violent, and personally sensitive material. We demonstrate that these models respond to harmful prompts by generating inappropriate content, which frequently displays troubling biases, such as the disproportionate portrayal of Black individuals in violent contexts. Our findings demonstrate a complete lack of any refusal behavior or safety measures in the models observed. We emphasize the importance of addressing this issue as image generation technologies continue to become more accessible and incorporated into everyday applications.
Mental health symptoms in Chinese children with sleep disorders and association with parental emotions
Abstract Depression, anxiety, and stress are major mental health challenges during children’s development. In China, heightened sleep disorders (SD), parental expectations, and academic stress highlight the importance of this issue. A total of 6,635 SD child-parent dyads were included in analysis. Sleep quality and psychological variables were assessed using Pittsburgh Sleep Quality Index (PSQI), Depression Anxiety Stress Scales (DASS) and Satisfaction with Life Scale (SWLS). Children with SD exhibited significantly higher rates of depression, anxiety, stress and life dissatisfaction. We identified the core and bridge symptoms within the Chinese children mental health symptoms and explored their associations with parental mental health. Worthlessness and palpitations, exhibiting the highest centrality values, were identified as core symptoms in the SD group. Palpitations were associated with elevated parental anxiety and stress. Impending collapse associated with parental anxiety, emerging as a bridge symptom may aggravate the occurrence of depression, anxiety and stress comorbidity in children. These symptoms provide theoretical basis for the targeted psychological intervention of Chinese children with SD in the future.
Genome of a novel Fangshan bunya-like virus identified in mosquitoes from Shandong Province, China
Exploring the use of large language models for classification, clinical interpretation, and treatment recommendation in breast tumor patient records
Supervised model based polycystic ovarian syndrome detection in relation to vitamin d deficiency by exploring different feature selection techniques
Abstract Due to urbanization and modern lifestyle, most of women in today’s world are prone to Polycystic Ovarian Syndrome (PCOS), which is a hormonal disorder. Though the symptoms shown by this disease are often uncared, it seriously affects the reproductive health of women. Early detection of PCOS helps in managing several other attributes that are closely related to it. This article aims to study the impact of Vitamin D3 in PCOS and non-PCOS individuals. The goal is attained by building a tailored dataset with 1368 records and 43 attributes. Initially, the acquired dataset is pre-processed by handling missed values, outlier detection and data balancing by employing Probabilistic Principal Component Analysis (PPCA), Interquartile Range (IQR), Z-score standardization and SMOTE respectively. The significant features are selected by exploring different approaches such as filter based (Chi-Square, ANOVA), wrapper based (Electric Eel Foraging Optimization Algorithm) and embedded methods (LASSO, XGBoost). The selected features are utilized to train classifiers such as Random Forest (RF), k-Nearest Neighbour (k-NN), Decision Tree (DT) and Support Vector Machine (SVM). The experimental results show that the performance of EEFOA with RF prove the best accuracy rates of 98.8% with a F-measure of 98.19%. Explainable Artificial Intelligence (XAI) techniques such as SHAP and LIME are then employed to showcase the feature importance. It is observed that over 40% of PCOS patients are affected by deficiency and insufficiency of vitamin D3.