The nylon 66/nano-CaCO3 composites were prepared by melt blending on a twin-screw extruder. Scanning electron microscopy (SEM), polarized light microscopy (PLM), thermal loss (TGA) and differential scanning calorimetry (DSC) The effects of nanometer calcium carbonate on the polycrystalline behavior and thermal properties of nylon 66/nano CaCO3 composites were investigated. The results show that the nanometer calcium carbonate particles are dispersed in the nylon 66 matrix and exist in the form of aggregates. The nanometer calcium carbonate has the effect of heterogeneous nucleation, which can reduce the size of the spherules. The decomposition temperature of the nylon 66 is 400 ℃, the addition of nano-CaCO3 to reduce the decomposition temperature. At the same time, DSC test showed that the β-crystalline form in the material reduced the melting temperature of the material. The addition of nano-CaCO3 in the nylon 66 matrix resulted in the decrease of the crystallization temperature and the increase of the half-height width of the endothermic peak. The lower the crystallization temperature, the wider the crystallization temperature range.

This study examines the determinants of stunting prevention among toddlers in fishing families residing in the coastal areas of Bengkulu City. Utilizing a mixed-method approach, the research combined survey data from 70 respondents and in-depth interviews with 11 informants. Findings indicate that health behavior and genetic factors from health status, alongside education level and occupation from socioeconomic status, play pivotal roles in stunting prevention. Consumption patterns, particularly the consistent provision of animal protein and vegetables in daily meals, significantly contribute to the absence of stunting cases in the studied population. However, limited fruit intake persists due to economic barriers. The study underscores the necessity of integrated strategies, including nutrition education, enhanced access to nutritious foods, and economic support for fishing families, to sustain stunting prevention in coastal communities.

This research focused on the design and implementation of the flipped classroom approach for higher mathematics courses in medical colleges. Out of 120 students, 60 were assigned to the experimental group and 60 to the control group. In the continuous assessment, which included homework and quizzes, the average score of the experimental group was 85.5 ± 5.5, while that of the control group was 75.2 ± 8.1 (P < 0.05). For the final examination, the average score in the experimental group was 88.3 ± 6.2, compared to 78.1 ± 7.3 in the control group (P < 0.01). The participation rate of students in the experimental group was 80.5%, significantly higher than the 50.3% in the control group (P < 0.001). Regarding autonomous learning ability, the experimental group spent an average of 3.2 hours per week on self-study, compared to 1.5 hours in the control group (P < 0.005). Other potential evaluation indicators could involve the percentage of students achieving high scores (90% or above) in problem-solving tasks (25.8% in the experimental group vs. 10.3% in the control group, P < 0.05), and the improvement in retention of key concepts after one month (70.2% in the experimental group vs. 40.5% in the control group, P < 0.01). In conclusion, the flipped classroom approach holds substantial promise in elevating the learning efficacy of higher mathematics courses within medical colleges, offering valuable insights for educational innovation and improvement.

The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.

Tomato powdery mildew, fruit rot, and twig blight are all managed with Deltamethrin. Its residues could still be present in the crops, posing a health risk. The pesticide residue analysis, dissipation rate, and safety assessments were thus examined in green tomatoes. The analytical method for residue analysis was validated according to international standards. Tomato fruits and soil were used to study the dissipation of Deltamethrin 100 EC (11% w/w) at 12.5 g a.i ha⁻¹ for the recommended dose (RD) and 25.0 g a.i ha⁻¹ for the double of the recommended dose (DD). Ethyl acetate was used to extract residues from tomato fruit, and PSA and magnesium sulphate were used for cleanup.The fruits had recoveries ranging from 83% to 93% and the soil sample from 81.67% to 89.6%, with the limit of detection (LOQ) estimated at 0.01 mg kg⁻¹. The matrix effect (ME) was calculated to be less than 20% for the tomato fruits and the soil.Half-lives for RD and DD were 1.95 and 1.84 days, respectively. All sampling days for both doses had dietary exposures of residues below the maximum permissible intake (MPI) of 0.16 mg person⁻¹ day⁻¹. The most effective method of decontaminating tomato residue containing Deltamethrin is blanching.