Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

A direct, sensitive and efficient spectrophotometric method for the determination of nitrofurantoin
drug (NIT) in pure as well as in dosage form (capsules) was described. The suggested method was
based on reduction NIT drug using Zn/HCl and then coupling with 3-methyl-2-benzothiazolinone
hydrazone hydrochloride (MBTH) in the presence of ammonium ceric sulfate. Spectrophotometric
measurement was established by recording the absorbance of the green colored product at 610 nm.
Using the optimized reaction conditions, beer’s law was obeyed in the range of 0.5-30 μg/mL, with
good correlation coefficient of 0.9998 and limits of detection and quantitation of 0.163 and 0.544
μg/mL, respectively. The accuracy and

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

Euphemism is an important linguistic phenomenon that tends to soften written or oral expressions. Thus, when translators or interpreters face expressions including euphemism, they need to know how to deal with them. The problem of the current paper lies in the effect of rendering euphemistic expressions inaccurately, as such expressions represent the cultural and terminological sense of the original language. Thus, rendering them improperly will affect the sense of the interpreted speech. For this, it is essential for translators in general and simultaneous interpreters in particular to know the importance of utilizing euphemism in the simultaneous interpreting field, which is the main aim of this paper. To this end, a systematic review

Hazardous materials, heavy metals, and organic toxins released into the environment have caused considerable harm to microbes, plants, animals, and humans. Wastewater is one of the most contaminated ecosystems due to heavy metals emitted mostly by human activity. Bioremediation of wastewater is an ecologically acceptable and cost-effective method of removing heavy metals from sewage; the general purpose of this study is to analyse the dependability of anaerobic sludge biomass in removing sulfur compounds and heavy metals from waste water. The anaerobic sludge biomass evaluated in this work was taken from a wastewater treatment plant (WWTP) in Al-Rustumiya, Baghdad, and grown in the mineral medium for anaerobic growth. In serum bottl