MXene (Ti₃C₂T_x) has emerged very recently as an interacting material for surface plasmon resonance (SPR) configuration. It was discovered that Ti₃C₂T_x can facilitate the adsorption of biomolecules due to its higher binding energies, stronger interaction between matter and light, and larger surface area. In this work, a two-dimensional Ti₃C₂T_x and silicon layer-based SPR refractometric sensor is proposed for the sensitive and fast detection of milk fat concentration due to the high significance of this issue to people all over the world. The proposed SPR structure employs BK7 (BK7 is a designation for the most common Borosilicate Crown glass used for a variety of applications in the visible range) as a coupling prism and silver as a metal layer. The layer thicknesses and the number of Ti₃C₂T_x sheets are optimized for the highest performance. The highest reached sensitivity is 350 deg./RIU with 50 nm silver and 4 nm silicon with a monolayer of Ti₃C₂T_x, which is ultra-high sensitivity compared to the latest work that utilizes SPR configuration. The proposed SPR-based sensor’s ultra-high sensitivity makes it more attractive for usage in a variety of biosensing applications.

The rapid advancement of artificial intelligence (AI) has led to its increasing integration into academic environments, raising critical questions about its educational implications. This study investigates the use of AI tools among university students in Jordan, focusing on platforms such as ChatGPT, Google Bard, Microsoft Bing, and Meta AI. A convergent-parallel mixed-methods design was employed, with quantitative (closed-ended) and qualitative (open-ended) data collected concurrently through an online survey distributed over two months. A total of 337 valid responses were obtained from students across 27 universities. The survey explored demographic characteristics, chatbot awareness and use, perceived benefits and challenges, ethical concerns, and future intentions. Results indicate that ChatGPT is the most recognized (94.3%) and widely used (90.4%) tool, while Meta AI is the least utilized (7.8%). Approximately 89% of students reported using AI tools for academic tasks, and 86.6% perceived them as educationally beneficial. However, only 39.7% believed these tools significantly improved their understanding, while 57.6% reported a positive impact on academic performance. These findings reveal a growing trend of AI integration into student study practices in Jordan, highlighting both its practical advantages and the need for further inquiry into its pedagogical value and ethical use.

Artificial intelligence tools are rapidly growing in education, highlighting the imperative need for a thorough and critical evaluation of their performance. To this aim, this study tests the effectiveness of ChatGPT and Google Bard in answering a range of questions within the engineering and health sectors. True/false, multiple choice questions (MCQs), matching, short answer, essay, and calculation questions are among the question types investigated. Findings showed that ChatGPT 4 surpasses both ChatGPT 3.5 and Google Bard in terms of creative problem-solving and accuracy across various question types. The highest accuracy achieved by ChatGPT 4 was in true/false questions, reaching 97.5%, while its least accurate performance was noted in calculation questions with an accuracy of 82.5%. Prompting both ChatGPT and Google Bard to provide short responses apparently prevented them from hallucinating with unrealistic or nonsensical responses. The majority of the problems for which ChatGPT and Google Bard provided incorrect answers demonstrated a correct problem-solving approach; however, both AI models struggled to accurately perform simple calculations. In MCQs related to health sciences, ChatGPT seemed to have a challenge in discerning the correct answer among several plausible options. While all three tools managed the essay questions competently, avoiding any blatantly incorrect responses (unlike with other question types), some nuanced differences were noticed. ChatGPT 3.5 consistently adhered more closely to the essay prompts, providing straightforward and essential responses, while ChatGPT 4 demonstrated superiority over both models in terms of adaptability. ChatGPT4 fabricated references, creating nonexistent authors and research titles in response to prompts for sources. While utilizing AI in education holds a promise, even the latest and most advanced versions of ChatGPT and Google Bard were not able to accurately answer all questions. There remains a significant need for human cognitive skills and further advancements in AI capabilities.

Medical technology companies have focused on gait analysis and monitoring for several years due to their importance in the diagnosis of various movement abnormalities. Studying pressure distribution on the foot is very important for the detection of abnormalities, unwanted symptoms, and consequences. This paper aims to design a wearable, low-cost, and real-time gait cycle monitoring system, based on a Flexiforce sensor. In the proposed design, eight force sensors were attached to the insole to estimate the pressure distribution on the foot. Pressure distribution monitoring helps in the estimation of foot disorders and assists in the design of medical shoes for manipulating pressure into the right positions. Sensors were connected to an appropriate microcontroller for real-time monitoring. MATLAB was used to visualize and simulate the real-time plantar pressure variation through static and dynamic states. The obtained experimental results show that the system was stable in both static and dynamic measurements, which could be used to estimate the pressure distribution on the foot.

This study presents a real-time, vision-based hand gesture UAV control system, enhancing drone accessibility and usability for non-experts.