One of the most important techniques for preparing nanoparticle material is Pulsed Laser Ablation in Liquid technique (PLAL). Carbon nanoparticles were prepared using PLAL, and the carbon target was immersed in Ultrapure water (UPW) then irradiated with Q-switched Nd:YAG laser (1064 nm) and six ns pulse duration. In this process, an Nd:YAG laser beam was focused near the carbon surface. Nanoparticles synthesized using laser irradiation were studied by observing the effects of varying incident laser pulse intensities (250, 500, 750, 1000) mJ on the particle size (20.52, 36.97, 48.72, and 61.53) nm, respectively. In addition, nanoparticles were characterized by means of the Atomic Force Microscopy (AFM) test, pH easurement

The eggshell cuticle is the proteinaceous outermost layer of the eggshell which regulates water exchange and protects against entry of micro-organisms. Outer eggshell and cuticle protein was extracted from domestic chicken. The aim of the research is to find out the effect of the treated and untreated nano particles of egg shells with micro wave cold plasma on the effectiveness of E. coli (negative bacteria) that infect the skin and measure the diameter of bacterial inhibition zone, the eggshell has been prepared by a chemical method (sol gel) and measure the level of acidity and the PH is neutral. The result of Atomic Force Microscope (AFM) shows that the particles diameters become smaller with nano-particles solution than for egg

Leishmaniasis is endemic ofIraq in both cutaneous and visceral form. The available tools for diagnosis and detection of Leishmaniaare nonspecific and may interfere with other species. In this study, Polymerase Chain Reaction (PCR) has been used to identify Iraqi isolate of visceral leishmaniasis (MHOM/ IQ/2005/MRU15) which a previously diagnosed by classical serological tests. PCR amplificationwas carried out using species-specific primers of Leishmania donovani. Four primer pairs of mini-circle DNA and ITS-1 were used.13A/13B, which is used to identify Leishmaniaas a genus, NM12, LITSR/L5.8S and BHUL18S, were used to detect the sub species of L. donovani.The result ofPCR

ِabstract:In this research we prepared nanofibers by electrospinning from poly (Vinyl Alcohol) /TiO2. The spectrum of the solution (Emission) was studied and found to be at 772 nm, several process parameters were such as concentration of TiO2 , and the effect of distance from nozzle tip to the grounded collector (gap distance). The result of the lower concentration of, the smaller the diameter of nanofiber is. Increasing the gap distance will affect nanofibers diameter.

The biochar prepared from sawdust raw material was applied in this study for the treatment of wastewater polluted with methyl orange dye. The effect of pH (2-11), initial concertation (50-250 mg/L) and time were studied. The isotherm of Langmuir, Frendluch and temkin models studied. The Langmuir model was the best to explain the adsorption process, maximum uptake was 136.67 mg/g at 25C^o of methyl orange dye. Equilibrium reached after four hours of contact for most adsorbents.The values of thermodynamic parameters ∆G were negative at various temperatures, so the process spontaneous, while ∆H values were 16683 j/mol and ∆S values was 60.82 j/mol.k.

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