This study compared the clinicopathological, immunohistochemical characteristics and Epstein-Barr virus (EBV) detection of Burkitt's lymphoma (BL) in the abdomen and jaw of Iraqi patients. A cohort/retrospective study was carried out between August and September 2024 using 25 tissue blocks (14 gnathic and 11 abdominal BL) from the Oral and Maxillofacial Laboratory, University of Baghdad, College of Dentistry, and the National Centre for Educational Laboratories. The sections were stained with haematoxylin and eosin (H&E), while CD10, CD20, Bcl-2, BCl-6, C-Myc and Ki-67 markers were used for diagnosis. The DNA detection of the EBV was performed by polymerase chain reaction (PCR). The tumours showed 22 classical and 3 atypical histologi

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

At the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat

As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

The aim of this study is to achieve the best distinguishing function of the variables which have common characteristics to distinguish between the groups in order to identify the situation of the governorates that suffer from the problem of deprivation. This allows the parties concerned and the regulatory authorities to intervene to take corrective measures. The main indicators of the deprivation index included (education, health, infrastructure, housing, protection) were based on 2010 data available in the Central Bureau of Statistics

Greenhouses are provide that produce of vegetable in non times seasons production by controlling the various environmental factors that appropriate atmosphere in temperature and humidity for the growth of plants in the plastic houses and owner plastic.
The objective of this research is to study of the most important natural and human factors affecting the Greenhouses in the province of Baghdad and study geographic distribution for the Greenhouses in the province.
Some properties on curriculum geographical descriptive analytical that used in describe and analysis of data and information that could be available from Directorate of agriculture in Baghdad to 2014. As it turns out that district of Mahmudiya acquired (45.3%) of the total

Abstract:

           The great importance that distinguish these factorial experiments made ​​them subject a desirable for use and application in many fields, particularly in the field of agriculture, which is considered the broad area for experimental designs applications.

            And the second case for the factorial  experiment, which faces researchers have great difficulty in dealing with the case unbalance we mean that frequencies treatments factorial  are not equal meaning (that is allocated a number unequal of blocks or units experimental per tre