The hydrolysis of urea by the enzyme urease is significant for increasing the irroles in human pathogenicity, biocementation, soil fertilizer, and subsequently in soil improvement. This study devoted to the isolation of urease from urea-rich soil samples collected from seven different locations. Isolation of the various bacterial species was conducted using nutrient agar. The identity of isolated urease was based on morphological characteristics and standard microbiological and biochemical procedures. The urease producing strains of bacteria were obtained using the urease hydrolysis test. The bacterial isolates produced from soil samples collected from different environments and treated by different morphological processes helped in precipitation of large calcium carbonate (CaCO3) crystal aggregates precipitated within bacterial colonies grown on agar. The different microbial species and functional attributes produced striking differences in the morphology of precipitated crystals. The phylogenetic sequencing of 16S ribosomal RNA genes produced several isolates that are mostly related to the Bacillus group. One strain of promising results was selected and the environmental and nutritional conditions were characterized. The growth curve of the selected strain with an optimized condition was investigated.
The current study aims to develop a teaching design in accordance with cluster thinking strategies and explore the effect of this teaching design on students’ achievement in science. To this end, the null hypothesis was adopted: there is no statistically significant difference at the level of (0, 05) between experimental group who adopted the teaching design in learning science and control group who follow the traditional method in learning the same subject. To test the null hypothesis, total of (74) students from Al-Alaama Hussain Mahfooth intermediate school were selected intentionally for the academic year 2016-2017. The sample divided into two equal groups when all the variables (age, prior achievement of science,
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Background: Osteoporosis is a systemic skeletal disorder that has an impact on general health, dental health and salivary composition. The mineralization of teeth happens simultaneously with that of the skeleton, but if mineral metabolism is disrupted, tooth failures will resemble those that affect bone tissue. Vitamin D plays a key role in bone and tooth mineralization.
Objective: to evaluate the impact of osteoporosis on teeth decay in relation to salivary vitamin D among menopause in Baghdad city.
Subjects and Methods: This study was cross sectional study. The study group consists of
... Show MoreBackground: During pregnancy many physiological, anatomical and biochemical changes take place that affect almost all body systems. In the oral pregnant women have serious changes such as more sever dental caries. This study was conducted to measure dental caries severity and selected salivary variables (salivary flow rate, PH and viscosity)and to find the relation of dental caries with these salivary variables. Subjects, materials and methods: The study group consisted of 60 pregnant women that were divided into three equal groups according to trimester (20 pregnant women in each trimester).They were selected randomly from the Maternal and Child Health Care Centers in Baghdad city, the age range was 20-25 years. In addition to 20 unmarried
... Show MoreBackground/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to
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The objective of this study is to measure the impact of financial development on economic growth in Iraq over the period (2004-2018) by applying a fully corrected square model (FMOLS) Whereas, a set of variables represented by (credit-to-private ratio of GDP, the ratio of money supply in the broad sense of GDP, percentage of bank deposits from GDP) were chosen as indicators for measuring financial development and GDP to measure economic growth.
Major tests have been carried out, such as the stability test (Unite Root Test), the integration test (Cointegration). Results of the study showed that there
... Show MoreThis paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining
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