The Herby gel are products developed to relieve stress and headaches, which often result from heavy work, a fast-paced lifestyle, or hot and humid weather. The patches are made from natural ingredients such as peppermint, neem leaves, gotu kola, aloe vera, and other herbs that effectively alleviate these symptoms. Free from alcohol, this product is safe to use and provides a cooling, soothing, and refreshing effect on the skin. It is easy to use, convenient to carry, and suitable for use in any situation, making it a practical solution for everyday discomfort.
ที่มา จากการศึกษาคุณสมบัติของสมุนไพรไทยที่มีประโยชน์ในการบรรเทาอาการต่างๆ โดยเฉพาะในเรื่องของการลดความร้อนและการบรรเทาอาการปวดหัว สมุนไพรบางชนิด เช่น ตะไคร้, มะกรูด, และใบสะระแหน่ มีคุณสมบัติในการเย็นและลดอาการปวดได้ดี ซึ่งได้ถูกนำมาใช้ในการพัฒนาเป็นผลิตภัณฑ์ที่สะดวกและใช้งานง่ายในรูปแบบของแผ่นเจลแปะหน้าผาก ที่สามารถแปะบนหน้าผากเพื่อช่วยลดอาการไม่สบายต่างๆ ได้อย่างรวดเร็วและปลอดภัย ความสำคัญ การตอบโจทย์ความต้องการของผู้บริโภคในยุคปัจจุบันที่ต้องการความสะดวกสบายและปลอดภัยในการบรรเทาอาการต่างๆ โดยไม่ต้องพึ่งพายาหรือวิธีการรักษาที่ซับซ้อน แผ่นเจลแปะหน้าผากที่ใช้สมุนไพรจากธรรมชาติช่วยให้ผู้ใช้สามารถบรรเทาอาการปวดหัวหรือไข้ได้อย่างรวดเร็วและมีประสิทธิภาพ อีกทั้งยังลดความเสี่ยงจากผลข้างเคียงที่อาจเกิดจากการใช้สารเคมีหรือยาที่มีสารเสพติด
คณะวิทยาศาสตร์
Recruitment is a crucial process that enables organizations to select candidates whose qualifications match the requirements of a given position. However, this process often faces challenges related to data management, delays, and human bias. This research aims to design and develop an intelligent web application for employee recruitment using artificial intelligence (AI) technology to evaluate and score candidates' suitability for job positions. The system leverages data analysis techniques on resumes and a qualification-matching process based on predefined criteria. Developed using Agile principles, the system employs Natural Language Processing (NLP) to analyze resumes, assess candidates’ qualifications, skills, and experience, and utilizes Machine Learning to predict and rank suitability. The system consolidates data from multiple sources into a unified database to reduce redundancy and input errors. Additionally, it presents insights through a dashboard, enabling HR teams to make more effective hiring decisions.
คณะวิศวกรรมศาสตร์
In this project, we introduce Power Grid Analyzer (PGAz), an open-source software package based on MATLAB, specifically designed for analyzing and controlling future power grids. Initially, PGAz is equipped with four fundamental features: power flow (PF), optimal power flow (OPF), small-signal stability analysis (SSSA), and time-domain simulation (TS). At this stage, Part I concentrates on the development of PF and OPF. The formats of our developed tool are presented, along with its command prompts. In this part, we have developed several conventional yet effective methods in the PGAz package to address PF and OPF problems, including techniques such as the Newton-Raphson method, Gauss-Seidel method, Interior Point Method, Iwamoto’s method, Fast Decoupled Load Flow, Genetic Algorithm, and Particle Swarm Optimization. Additionally, it emphasizes important aspects, algorithms, and various case studies that have been tested against IEEE benchmarks ranging from the IEEE 5-bus to the IEEE 300-bus test systems. The results demonstrate the capabilities of PGAz for future educational and research applications in PF and OPF. Finally, we outline a plan for developing Part II, which will mainly focus on SSSA and TS.
คณะวิทยาศาสตร์
Cancer remains a major global health challenge as the second-leading cause of human death worldwide. The traditional treatments for cancer beyond surgical resection include radiation and chemotherapy; however, these therapies can cause serious adverse side effects due to their high killing potency but low tumor selectivity. The FDA approved monoclonal antibodies (mAbs) that target TIGIT/PVR (T-cell immunoglobulin and ITIM domain/poliovirus receptor) which is an emerging immune checkpoint molecules has been developed; however, the clinical translation of immune checkpoint inhibitors based on antibodies is hampered due to immunogenicity, immunological-related side effects, and high costs, even though these mAbs show promising therapeutic efficacy in clinical trials. To overcome these bottlenecks, small-molecule inhibitors may offer advantages such as better oral bioavailability and tumor penetration compared to mAbs due to their smaller size. Here, we performed structure-based virtual screening of FDA-approved drug repertoires. The 100 screened candidates were further narrowed down to 10 compounds using molecular docking, with binding affinities ranging from -9.152 to -7.643 kcal/mol. These compounds were subsequently evaluated for their pharmacokinetic properties using ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, which demonstrated favorable drug-like characteristics. The lead compounds will be further analyzed for conformational changes and binding stability against TIGIT through molecular dynamics (MD) simulations to ensure that no significant conformational changes occur in the protein structure. Collectively, this study represents the potential of computational methods and drug repurposing as effective strategies for drug discovery, facilitating the accelerated development of novel cancer treatments.