V. Kharchenko, A. Grekhov and V. Kondratiuk, “Cognitive Adaptation of Modulation for Improving Noise Resistance of a Tropospheric UAV Channel,” Trans. Appl. Sci. Eng. Technol., vol. 2, no. 1, pp. 1-8, 2026.

In modern operational conditions of unmanned aerial vehicles (UAVs), the stability and reliability of communication channels are becoming key factors in the successful completion of missions. Operation in a dynamically changing radio environment, including the influence of natural interference and electronic warfare (EW), is especially relevant. Traditional communication systems with a fixed modulation scheme cannot effectively respond to changes in channel parameters, such as signal level, signal-to-noise ratio (SNR), and the presence of interference. This leads either to excessive errors (with excessive modulation) or to an unjustified loss of throughput (with increased reliability under good conditions). One of the key areas for improving noise immunity is the cognitive adaptation of modulation. To study the influence of cognitive adaptation on noise immunity in the UAV communication channel, an original model, “Base Station-Tropospheric Drone-UAV,” was built using the MATLAB Simulink software. The dependences of the SNR ratio on the Free Space Path Loss (FSPL) for different types of signal modulation and noise temperatures were obtained. The calculated interrelated sequences of FSPL, SNR, and modulation were used to adapt the modulation in accordance with changing transmission conditions. The model was trained on the obtained data and then used for modulation adaptation. Python code is given that uses the Random Forest Classifier model to predict the modulation type.

V. Agrawal, H. Sinha, P. Sharma, D. Mehta, D. Sheth, H. Shah and Y. Jogi, "NewGen HeadGear: Designing an Integrated Smart Helmet to Address Modern Road Safety Challenges," Trans. Appl. Sci. Eng. Technol., vol. 1, no. 2, pp. 1–5, 2025.

Two-wheeler accidents continue to claim thousands of lives every year, with a large proportion of these tragedies being entirely preventable. Riders who skip helmets, drive after drinking, or speed on busy roads create dangers not only for themselves but for everyone sharing the road. Equally troubling is the fact that when accidents do happen, help often arrives too late simply because no one was notified in time. This paper introduces the NewGen HeadGear, a smart helmet system built by a team of Grade 10 students at Witty International School, Borivali. The design combines a microcontroller, motion sensor, alcohol detector, GPS unit, and a wireless communication module to tackle five interconnected safety problems in one compact device. A companion mobile application lets parents set speed limits and receive instant alerts, while an RFID tag built into the helmet allows traffic officers to verify a rider's documents without any paperwork. The goal of this project is to show that student-level innovation, when grounded in real-world problems and supported by off-the-shelf technology, can produce ideas worthy of serious consideration by engineers, policymakers, and road safety advocates.

L. Bertran, C. Aguilar, T. Auguet and C. Richart, “Unraveling the Lack of Correlation between RBP4 and MASLD: Insights from Gene Expression and Serum Level Analysis,” Trans. Appl. Sci. Eng. Technol., vol. 1, no. 2, pp. 1-6, 2025.

Although previous evidence supports the involvement of retinol binding protein 4 (RBP4) in metabolic dysfunction-associated steatotic liver disease (MASLD), there are conflicting reports. Our aim was to evaluate the role of RBP4 in MASLD among a homogeneous cohort of women with morbid obesity (MO). We recruited 180 women with MO, including 40 with normal liver (NL), 40 with simple steatosis (SS), and 100 with metabolic dysfunction-associated steatohepatitis (MASH). Serum levels of RBP4 were analyzed by an enzyme-linked immunosorbent assay (ELISA). RBP4 hepatic mRNA expression was evaluated by a quantitative polymerase chain reaction (qPCR). In this sense, we did not report significant differences in RBP4 circulating levels between hepatic histological groups. However, analyzing RBP4 hepatic mRNA expression, we observed decreased expression of RBP4 in MASH subjects compared to those with NL or SS. To conclude, in a homogeneous and sizeable cohort of women with MO and MASLD, our findings limit, contrary to previous proposals, the key role of RBP4 in relation to MASLD and MASH pathogenesis. Therefore, new studies are necessary in other study groups to validate the absence of this correlation.

A. Srivatsa, Kavya A.P., F. Fareesha, Lekhana G., Gowthami V. and Chandanashree Y.K., “Prototype for Stress-Based Viral Fever Prediction,” Trans. Appl. Sci. Eng. Technol., vol. 1, no. 2, pp. 1-12, 2025.

This paper presents the development of a prototype device for predicting viral fever by monitoring stress levels through cortisol detection. Research indicates a negative correlation between the immune system’s strength and prolonged high stress levels. As stress increases, the immune system weakens, making individuals more susceptible to viral fevers and infections. The primary goal of this study is to design a device that tracks stress levels by measuring cortisol, a neuroendocrine hormone released during stress. Our approach utilizes a synthetic form of cortisol to construct the prototype, employing infrared (IR) sensing technology with IR LEDs and photodiodes to detect cortisol levels. This innovative device aims to provide an early warning system for viral infections by continuously monitoring and analyzing stress-induced hormonal changes.