The growing interest in antioxidant-rich foods is driven by their potential to reduce the risk of chronic diseases such as cancer, cardiovascular conditions, and cellular degeneration. Ginger (Zingiber officinale), banana inflorescence (Musa paradisiaca L.), and roselle (Hibiscus sabdariffa L.) are herbal plants known for their high phenolic content, a crucial component in antioxidant activity. However, the bioactive compounds in these plants are often unstable when exposed to light, temperature, and oxygen, leading to a reduction in their efficacy. This study aims to investigate the optimal ratio of ginger, banana inflorescence, and roselle for encapsulation in liposomes—a technique designed to enhance the stability of bioactive compounds and improve their delivery efficacy. The research evaluates the antioxidant activity of the extracts using DPPH, ABTS, and FRAP methods, alongside total phenolic content (TPC) measurement. The most effective ratio for antioxidant activity will be selected for liposomal encapsulation, employing phospholipids as key structural components. The encapsulation efficiency (EE%) will be calculated to assess the effectiveness of the liposomal delivery system. The findings are expected to identify the optimal combination of ginger, banana inflorescence, and roselle that maximizes antioxidant potency and enhances the stability of bioactive compounds through liposomal encapsulation. This approach offers a promising strategy for developing herbal health supplements that maintain their biological properties over time.
การเสื่อมสภาพของเซลล์จากอนุมูลอิสระเป็นสาเหตุหลักที่นำไปสู่การเกิดโรคเรื้อรังต่าง ๆ เช่น โรคมะเร็ง โรคหัวใจ และการเสื่อมสภาพของเซลล์ในระบบต่าง ๆ ของร่างกาย ดังนั้นการใช้สารต้านอนุมูลอิสระจากธรรมชาติจึงเป็นวิธีหนึ่งในการลดความเสี่ยงจากการเกิดโรคเหล่านี้ ขิง ปลีกล้วย และกระเจี๊ยบ เป็นพืชที่มีสารต้านอนุมูลอิสระและสารฟีนอลิกที่มีคุณสมบัติในการป้องกันความเสื่อมของเซลล์ อย่างไรก็ตาม สารเหล่านี้อาจสูญเสียประสิทธิภาพเมื่อสัมผัสกับปัจจัยภายนอก เช่น แสง ความร้อน และออกซิเจน ดังนั้นการใช้เทคนิคการห่อหุ้มสารด้วยวิธีลิโพโซม จึงช่วยเพิ่มความเสถียรของสารสำคัญและเพิ่มประสิทธิภาพในการนำส่งสารไปยังจุดเป้าหมายจึงเป็นสิ่งสำคัญ
คณะบริหารธุรกิจ
CO Breathalyzer with Voice Response is the device to measured the level of CO residual in a person's lung who consume tobacco. Measuring residual CO in human breath can identify the tobacco addiction level instead of measuring nicotine in blood.
คณะวิศวกรรมศาสตร์
The Diabetes Meal Management Application is a digital health tool designed to empower Type 2 diabetic patients in managing their diet and blood sugar levels more effectively. With features like personalized meal recommendations, nutrient tracking, and seamless integration with wearable blood glucose monitors via Blood sugar measuring device (CGM), the application enables users to monitor glucose fluctuations in real time and adjust dietary choices accordingly. Built with the Flutter framework and supported by a backend of Express.js and MongoDB, the application prioritizes a user-friendly interface, ensuring easy navigation and encouraging consistent engagement with meal planning and health tracking. Preliminary user trials show that the application contributes to more stable blood sugar levels and improved adherence to dietary recommendations, helping users reduce health risks associated with diabetes complications. By offering a proactive approach to diabetes management, the application reduces the need for frequent clinical interventions, thus potentially lowering medical costs over time. This project highlights the promising role of digital health solutions in supporting personalized diabetes care, emphasizing the potential for scalable, user-centered interventions that foster long-term health improvements for diabetic patients.
คณะวิศวกรรมศาสตร์
This project aims to develop a conceptual prototype of a weapon aiming system that simulates an anti-aircraft gun. Utilizing an optical camera, the system detects moving objects and calculates their trajectories in real time. The results are then used to control a motorized laser pointer with two degrees of freedom (DoF) of rotation, enabling it to aim at the predicted position of the target. Our system is built on the Raspberry Pi platform, employing machine vision software. The object motion tracking functionality was developed using the OpenCV library, based on color detection algorithms. Experimental results indicate that the system successfully detects the movement of a tennis ball at a rate of 30 frames per second (fps). The current phase involves designing and integratively testing the mechanical system for precise laser pointer position control. This project exemplifies the integration of knowledge in electronics (computer programming) and mechanical engineering (motor control).