Evaluation of trace elements in Iraqi chewing gums are unavailable, particularly pollution of toxic elements, materials which change the values of PH in the Oral. Atomic Absorption Spectroscopy (AAS) were successfully employed to determine the concentration of 7 trace elements (essentially toxic and nonessential) and the PH, in thirteen different brands of chewing gum generally consumed in Iraq. Combined wet and dry digestion procedures were applied. Two types of heated graphite tubes were used, coated and uncoated tubes treated with tungsten solution. Result showed that Cu, Al and Zn were at very high levels in almost all brands whereas Mn was found to be high in brands A and O only.

In this research, a novel synthesis of CaONPs has been developed via an environmentally friendly, green method. Garlic extract (Allium sativum) was used as a green-reducing and stabilizing agent for CaONPs. The average particle size of CaONPs was approximately 24.42 nm. The synthesized CaONPs were identified by using Fourier transform infrared (FT-IR) spectroscopy, U.V.-vis spectrum, X-ray diffraction (XRD), Field Emission-Scanning Electron Microscopy (FE-SEM), Transmission Electron Microscopy, transmission electron microscopy (TEM), Energy Dispersive X-ray spectroscopy (EDX), Atomic Force Microscopy (AFM), and zeta potential (Zp) analysis. The current study highlights the notable applications for CaONPs. First, an antimicrobial assay revea

Background A prospective clinical study was
performed to compare the efficacy of the use of lowmolecular-
weight heparin group (enoxparin group)
with control group in the prevention of deep-vein
thrombosis after total knee arthroplasty.
Aim of the study: to assess the prevalence of DVT
after total knee arthroplasty and evaluate the
importance of the use of low molecular weight
heparin in the prevention of this DVT.
Methods Thirty-three patients undergoing total
knee arthroplasty were randomly divided into two
groups. One group consisted of 12 patients who
received no prophylaxis with an anticoagulant (the
control group), other group consisted of 21 patients
who received the low-molecular-weight h

The study searches for the possibility of using duckweed Lemna spp. to reduce the concentration of heavy metals (zinc and iron) in the wastewater of Baghdad by culturing two different densities of the plant with a fresh weights 5 and 10 g/l and without the plant under optimum uncontrolled conditions. The result showed that there was a significant differences at the possibility level of (p? 0.05) for the three treatments, as the highest percentages for zinc removal in the second day for the plant treatment of 5 g/l were 66.40%, while the highest percentage of iron removal were in the tenth days for the plant treatment 10 g/l were 80 %, and noticed that the increase of the heavy metals concentrations accumulated in the plant after bei

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

The research work involve preparation of activated carbon from Plant corn grain dry in the presence of some additive Residual of poly ethelenetereaphthalate.and the anather way Carbonization was conducted by mixing a known weight of the feedstock with variable quantity of the additive and fixed ratio of Potassium hydroxide. Carbonization completed using fusion in solid state in the absence of solvents. Feedstock and mainly Remnants of poly ethelenetereaphthalate were decompose thermally in a Small chains containing to naphthoxide radicals, these radicals can be connected with the Chains of activated carbon aiming to increase polarity ,This was found from the reaction it self . this research has been studying the product sample was eva

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th