This research paper explores the integration of Thermoelectric Generators (TEGs) as dual-function components in wearable devices, serving as both energy harvesters and fuzzy logic-enhanced actuators. The study presents experi-mental results highlighting the TEG's performance in harvesting energy from applied temperature gradients. The harvested energy can power the wearable device, addressing the demand for sus-tainable power sources in various fields including healthcare applications. Additionally, the paper introduces the application of fuzzy logic systems to refine the TEG's role as an actuator. It is worth noting that the TEG's voltage output is utilized to measure temperature variations, and the fuzzy logic system interprets these inputs to optimize alert system responses. This amalgamation of TEGs and fuzzy logic offers a novel approach to enhance the accuracy and responsiveness of temperature-sensitive alert systems. The research findings provide valuable insights into the potential of this integrated system for advancing wearable and medical device technology.

This paper investigates the vibrations at Castello Normanno-Svevo Aci Castello in Catania, Italy. The study is conducted within the context of examining vibration levels and frequency distribution in environments of historical and artistic significance. The objectives focus on two key aspects related to cultural heritage: measuring mechanical vibrations for the preventive conservation of artifacts and structures of historical and artistic interest and exploring the potential use of such kinetic energy to power autonomous systems. This paper specifically focuses on a preliminary study of the outdoor environment. Based on the vibrational analysis, the successive aim is to develop optimized MEMS and generate transducers tailored to the specific context and area of interest. The analysis concentrated on time-domain signals along the X, Y, and Z axes, with an in-depth examination of the Z axis using Fast Fourier Transform (FFT) and Power Spectral Density (PSD). The results revealed consistent vibration patterns across all three axes, with the vertical axis (Z) being more significantly influenced by outdoor-induced vibrations, primarily caused by sea movements and wind. The findings illustrate the vibration levels at this location and the relevant spectral distribution for future applications in designing optimized electromechanical converters, energy harvesting systems, and autonomous measurement nodes suitable for operation in this environment.

Controlling patients with Alzheimer's disease is very challenging. This paper presents a novel approach for enhancing the efficiency of wireless power transfer systems in smart devices used for managing patients with Alzheimer's disease. The pro-posed system contains a conical coil as a transmitter instead of the conventional circular coil shape to maximize coupling and ensure reliable power transfer. Through this paper, we have modeled a conical coil for the proposed system to reach its maximum coil quality factor. For certain frequencies, the proper inductance and resistance of the primary coil value are deduced by a mathematical expression from its length expression. This method has the potential to significantly enhance the effectiveness of technological solutions aimed at assisting individuals affected by this disease. This paper demonstrates that the quality factor of the system using a conical coil as a transmitter can be maximized, resulting in improved performance compared to traditional circular coil shapes. The findings suggest that this innovative coil design has promising implications for advancing WPT systems in healthcare applications for Alzheimer's patients.

Alzheimer’s disease is characterized by two Key pathophysiological features, which are neurofibrillary tangles and senile plaques. In this study, we propose a novel nanorobot model aimed at the early detection of Alzheimer’s disease. As an initial step, we conducted an experimental investigation into the polymorphism of the TREM2 gene’s exons to determine allelic and genotypic frequencies, highlighting its correlation with Alzheimer’s disease. Our case-control study involved a sample of 124 Tunisian subjects, divided into two groups: 64 patients diagnosed with Alzheimer’s and 60 age-matched controls, averaging 67 years. Each participant underwent a comprehensive neurological examination, neuropsychological assessment, brain imaging, and molecular analysis. For the genetic component of our study, we employed PCR and sequencing techniques, identifying the rs2234253 variant in exon 2 and a novel intronic variant in intron 4. Our findings indicate that the TREM2 gene significantly contributes to the risk of developing Alzheimer’s disease. Based on these results, we present our proposed nanorobot model designed for the early detection of this condition, detailing its potential applications in monitoring and diagnosis.

This study investigates the vibrations at the Castello Svevo-Normanno in Aci Castello (Catania), focusing on its historical and cultural significance. The research aims to analyze vibration levels and frequency distribution to achieve two objectives: protecting historical artifacts and structures through preventive vibration analysis and exploring the use of kinetic energy for powering autonomous systems. The study specifically focuses on the indoor context to understand its unique vibrational characteristics. Measurements were recorded along the X, Y, and Z axes, with detailed analysis of the Z axis using Fast Fourier Transform (FFT) and Power Spectral Density (PSD). The results revealed consistent vibration patterns across all axes, with the Z axis significantly influenced by environmental factors such as wind and sea movement. These findings provide valuable insights for designing optimized energy harvesting systems, electromechanical converters, and monitoring devices suitable for operation in this specific historical context.

This study explores the application of fuzzy systems as universal approximators for nonlinear functions, focusing on mono-variable and scalable to multi-variable functions. Ensuring error-free approximations through quadratic terms, our method-ology emphasizes reliability. Shifting to practicality, we investi-gate thermoelectric generators' dynamic response to temperature fluctuations. The research underscores fuzzy systems' precision in modeling TEG behavior, validating applicability and accuracy through diverse temperature scenarios.