Background: Pyogenic granuloma is a hyperplastic benign tumor. The most common intra-oral site is marginal gingiva. It is often occurred in the second decade of life, it has a strong tendency to recur after simple excision.

The aim of study: to evaluate the therapeutic advantages of diode laser (810-980 nm) in intraoral Pyogenic granuloma management.

Materials and method: A total of 28 patients (14 men and 14 females) were enrolled in this study and had their pyogenic granuloma surgically removed using a diode laser. All of the patients were given local anesthetic and went through the identical surgical procedure (cartridge containing 1 percent lidocaine with epinephrine 1:

This study has contributed to understanding a delayed prey-predator system involving cannibalism. The system is assumed to use the Holling type II functional response to describe the consuming process and incorporates the predator’s refuge against the cannibalism process. The characteristics of the solution are discussed. All potential equilibrium points have been identified. All equilibrium points’ local stability analyses for all time delay values are investigated. The system exhibits a Hopf bifurcation at the coexistence equilibrium, which is further demonstrated. The center manifold and normal form theorems for functional differential equations are then used to establish the direction of Hopf bifurcation and the stability of the per

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

The electrical performance of bottom-gate/top source-drain contact for p-channel organic field-effect transistors (OFETs) using poly(3-hexylthiophene) (P3HT) as an active semiconductor layer with two different gate dielectric materials, Polyvinylpyrrolidone (PVP) and Hafnium oxide (HfO2), is investigated in this work. The output and transfer characteristics were studied for HfO2, PVP and HfO2/PVP as organic gate insulator layer. Both characteristics show a high drain current at the gate dielectric HfO2/PVP equal to -0.0031A and -0.0015A for output and transfer characteristics respectively, this can be attributed to the increasing of the dielectric capacitance. Transcondactance characteristics also studied for the three organic mater

Fullerene nanotube was synthesized in this research by pyrolysis of plastic waste Polypropylene (PP) at 1000 ° C for two hours in a closed reactor made from stainless steel using molybdenum oxide (MoO₃) as a catalyst and nitrogen gas. The resultant carbon was purified and characterized by energy dispersive X-ray spectroscopy (EDX), X-ray powder diffraction (XRD). The surface characteristics of C₆₀ nanotubes were observed with the Field emission scanning electron microscopy (FESEM). The carbon is evenly spread and has the highest concentration from SEM-EDX characterization. The result of XRD and FESEM shows that C₆₀ nanotubes are present in Nano figures, synthesized at 1000 ° C and with pyrolysis tempera

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample