This study aimed to investigate the effectiveness of additive manufacturing (AM)-based teaching methods compared to traditional methods for teaching the Archimedes experiment in science education. Results showed that the AM method was significantly more effective in enhancing students’ understanding of the Archimedes principle and their ability to apply it to real world scenarios. The customisable and hands on nature of 3D printing also led to higher levels of student engagement and enjoyment. However, limitations were identified in terms of the time, resources, and cost required to set up the 3D printing experiment. Despite these limitations, our study suggests that AM has the potential to revolutionise science education by providing students with a more engaging, hands on, and customisable learning experience.

Aim: The purpose of this research is to analyze the neutrophil-to-lymphocyte ratio (NLR) to define prognostic factors in patients with breast cancer and to analyze the NLR values among stages, grades, and fractions. Methods: The data retrieval period was from October 2018 to June 2020. The study included 56 patients who were part of the research. The mean age of patients was 53.42 years. Results: On average, NLR after radiotherapy was higher than before treatment. Moreover, the 5-year overall survival rate for breast cancer patients treated with radiotherapy was 81%. Conclusions: Based on the NLR results for patients with breast cancer, it is confirmed that the ratio of patients with poor prognosis compared to those with good prognosis is 3.3 to 1. Specifically, all stages of breast cancer showed an increase in NLR after treatment. The exception was stage III, which showed lower NLR values after treatment and, consequently, a better prognosis of the disease.

This study aimed to investigate the effectiveness of additive manufacturing-based teaching methods compared to traditional methods for teaching the Archimedes experiment in science education. Results showed that the additive manufacturing method was significantly more effective in enhancing students\' understanding of the Archimedes principle and their ability to apply it to real-world scenarios. The customizable and hands-on nature of 3D printing also led to higher levels of student engagement and enjoyment. \nHowever, limitations were identified in terms of the time, resources, and cost re-quired to set up the 3D printing experiment. Despite these limitations, our study suggests that additive manufacturing has the potential to revolutionize science education by providing students with a more engaging, hands-on, and customizable learning experience.

The accurate calibration of radiochromic films is critical for high dose rate (HDR) brachytherapy dosimetry. Conventional workflows frequently rely on manually determined regions of interest (ROIs), which might increase operator variability. In this investigation, Gafchromic EBT3 films were irradiated under clinical settings at nominal doses of 0–10 Gy and evaluated using a MATLAB (R2024b)-based tool that allows for both manual and automated ROI selection. The calibration curves were modeled with a second-order polynomial and rational model, and performance was assessed using statistical measures. The study found that the rational model fits better than the polynomial model. Additionally, the automatic ROI approach outperformed the manual method in both models, resulting in higher calibration accuracy and reproducibility (R² = 0.999, RMSE = 0.118 Gy, MAE = 0.103 Gy vs. R² = 0.986, RMSE = 0.448 Gy, MAE = 0.388 Gy). Although manual ROI occasionally produced greater dose–response slopes at higher doses, it was more susceptible to operator bias and film non-uniformity. In contrast, automatic ROI reduced variability by consistently picking homogeneous sections, resulting in steady curve fitting across the entire dose range. Furthermore, a companion module transformed calibrated films into 2D false-color maps and 3D dosage surfaces, allowing for visual assessment of dose uniformity, detection of scanner-related aberrations, and quantitative verification for quality assurance. These findings demonstrate that automated ROI selection provides a more stable and reproducible foundation for film calibration in HDR brachytherapy, minimizing operator dependency while facilitating routine clinical quality assurance.