Traditional healthcare for chronic wounds and Cold Atmospheric Plasma (CAP) treatments relies on passive dressings and large-volume stationary equipment operating with open-loop systems, which severely limits their use and confines it to specialized clinical environments. To address the lack of active thermal safety mechanisms in mobile devices, this research proposes a wearable smart plasma patch equipped with a closed-loop adaptive electronic control system to ensure safe patient care and treatment at home. The smart patch integrates real-time analog biosensors to continuously monitor skin temperature and relative humidity. An algorithm running on a microcontroller dynamically adjusts the high-voltage plasma parameters using Pulse Width Modulation (PWM). The system's performance was rigorously verified using a combined simulation framework for mixed signals, with Proteus software for electronic circuits and MATLAB/Simulink for biodynamics and thermodynamics. The simulation results demonstrated the controller's high efficiency in maintaining a precise, optimal treatment environment (36–37 °C, humidity ∼60%) and preventing thermal accumulation. In addition, the effectiveness of an active hardware protection mechanism was demonstrated, with an emergency high-voltage cut-off successfully implemented within a standard 20-ms time window upon detecting thermal hazards. In conclusion, this compact and intelligent design effectively limits the risk of tissue thermal necrosis, providing a powerful and independent safety indicator in the design of modern, scalable medical devices.
Abstract
The current study was carried out to reveal the plasma parameters such as ,the electron temperature ( ), electron density (ne) , plasma frequency (fp), Debye length ( ) , Debye number ( for CdS to employ the LIBS for the purpose of analyzing and determining spectral emission lines using . The results of electron temperature for CdS range (0.746-0.856) eV , the electron density(3.909-4.691)×1018 cm-3. Finally ,we discuss plasma parameters of CdS through nano second laser generated plasma .
This study aims to analyze spectra in real-time for λ Draconids, σ Hydrids, μ Virginid, and one sporadic meteor using spectroscopic chemical analysis and diagnose plasma parameters. Good-resolution spectroscopy and a CCD camera for meteor observation were used concurrently to examine the ablation spectra of these meteorites in situ. The Boltzmann and Lorentz methods were then used to determine the temperature and density of electrons, the length of Debye, and the frequency of plasma. Furthermore, spectra data can be analyzed and compared to data from other sources. Spectrum tests can be utilized to identify the chemical structure of meteorites' plasma.
In this work, we studied the effect of power variation on inductively coupled plasma parameters using numerical simulation. Different values were used for input power (750 W-1500 W), gas temperature 300K, gas pressure (0.02torr), 5 tourns of the copper coil and the plasma was produced at radio frequency (RF) 13.56 MHZ on the coil above the quartz chamber. For the previous purpose, a computer simulation in two dimensions axisymmetric, based on finite element method, was implemented for argon plasma. Based on the results we were able to obtain plasma with a higher density, which was represented by obtaining the plasma parameters (electron density, electric potential, total power, number density of argon ions, el
... Show MoreNon-thermal (low-temperature) plasma may act as an alternative approach to control superficial wound and skin infections when the effectiveness of chemical agents is weak due to natural pathogen or biofilm resistance. In this paper an atmospheric pressure plasma needle jet device which generates a cold plasma jet is used to measure the effectiveness of plasma treatment against different pathogenic bacteria and to test the individual susceptibility of pathogenic bacteria to non-thermal argon plasma. It is found that, Gram-negative bacteria were more susceptible to plasma treatment than Gram-positive bacteria. For the Gram-negative bacteria Pseudomonas aeruginosa, there were no survivors among the initial 1x108C.F.U (Co
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This paper presents the design of a longitudinal controller for an autonomous unmanned aerial vehicle (UAV). This paper proposed the dual loop (inner-outer loop) control based on the intelligent algorithm. The inner feedback loop controller is a Linear Quadratic Regulator (LQR) to provide robust (adaptive) stability. In contrast, the outer loop controller is based on Fuzzy-PID (Proportional, Integral, and Derivative) algorithm to provide reference signal tracking. The proposed dual controller is to control the position (altitude) and velocity (airspeed) of an aircraft. An adaptive Unscented Kalman Filter (AUKF) is employed to track the reference signal and is decreased the Gaussian noise. The mathematical model of aircraft
... Show MoreThe effected of the long transmission line (TL) between the actuator and the hydraulic control valve sometimes essentials. The study is concerned with modeling the TL which carries the oil from the electro-hydraulic servovalve to the actuator. The pressure value inside the TL has been controlled by the electro-hydraulic servovalve as a voltage supplied to the servovalve amplifier. The flow rate through the TL has been simulated by using the lumped π element electrical analogy method for laminar flow. The control voltage supplied to servovalve can be achieved by the direct using of the voltage function generator or indirect C++ program connected to the DAP-view program built in the DAP-card data acqu
... Show MoreThis paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback
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