The aim of this study is to investigate the ability of malachite green (MG) combined with 650nm diode laser to kill Candida albicans and to spectrally study the MG photodegradation after photodynamic therapy (PDT) spectrally. Cultures of Candida albicans were exposed to 40mW, 650 nm diode laser in the absence of MG. In PDT group, the MG was added to the Candida suspension for 5 min then exposed to diode laser for (5, 10, 15, 20) min at power density of 0.59W/cm2. The absorption spectrum of the photosensitized fungal suspension was obtained. The data were submitted to T-test (p<0.05). A 650nm diode laser in the presence of MG reduced the number of CFU/ml in 98.4%. Laser with 650nm alone and MG alone did not reduce significantly the num

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When laser light incident on biological tissue, it is either reflected from the
surface of the tissue (e.g. the skin) or scattered inside the tissue or absorbed .The laser light will be
absorbed by water, hemoglobin and melanin. Absorption is also highly dependent on wave-length of
laser radiation. The absorbed light is converted into kinetic energy leading to laser effect that when
appropriately applied can produce reaction ranging from incision, vaporization to coagulation. Aim of
the study: To evaluate the efficiency of diode Laser 810 ± 20nm in treatment of oral lesions. Methods:
6 patients (2 females and 4 males) with different oral lesions were treated in the hospital of specialized
surgeries by the use of dio

With the increasing rate of unauthorized access and attacks, security of confidential data is of utmost importance. While Cryptography only encrypts the data, but as the communication takes place in presence of third parties, so the encrypted text can be decrypted and can easily be destroyed. Steganography, on the other hand, hides the confidential data in some cover source such that the existence of the data is also hidden which do not arouse suspicion regarding the communication taking place between two parties. This paper presents to provide the transfer of secret data embedded into master file (cover-image) to obtain new image (stego-image), which is practically indistinguishable from the original image, so that other than the indeed us

Abstract

       The current study was carried out to reveal the plasma parameters such as ,the electron temperature ( ), electron density (n_e) , 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 .

Copper nanoparticles (CuNPs) were prepared with different diameters by sonoelectrodeposition technique using Electrodeposition process coupled with high-power ultrasound horn (Sonoelectrodeposition). The particle diameter of the CuNPs was adjusted by varying CuSO4 solution acidity (pH) and current density. The morphology and structure of the CuNPs were examined by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). It was found that the size of the produced copper nanoparticles ranged between 22 to 77 nm, where the diameter of CuNPs increases with reduction the solution acidity from 0.5 to 1.5 pH and increasing the current density of the deposition from 100 to 400 nm. Finally the produced CuNPs were pressed to fabricate disc

In this paper the behavior of the quality of the gradient that implemented on an image as a function of noise error is presented. The cross correlation coefficient (ccc) between the derivative of the original image before and after introducing noise error shows dramatic decline compared with the corresponding images before taking derivatives. Mathematical equations have been constructed to control the relation between (ccc) and the noise parameter.

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w