Reading is an interactive process that goes on between the reader and the text, resulting in comprehension. The text presents letters, words, sentences, and paragraphs that encode meaning. The reader uses knowledge, skills, and strategies to determine what that meaning is. Reading comprehension is much more than decoding; it results when the reader knows which skills and strategies are appropriate for the type oftext, and understands how to apply them to accomplish the reading purpose.Reading comprehension is important because without it reading is nothing more than tracking symbols on a page with your eyes and sounding them out leaving the reader with no information. Instead of promoting traditional approaches, reading should be taught in a more interactive and communicative manner. In this light, this study investigates the difficulties faced by engineering students in reading comprehension in a university setting where the medium of instruction and communication is not English, but where students are required to read textbooks in English. The participants are selected from College of Engineering/ University of Al-Mustansiriya to take the test. However, a standardized test is used to show the students‟ difficulties in reading comprehension. Two passages are used in the test, the first one is concerned with their specialization in engineering while the second is concerned with general topics. Data analysis is conducted through using one sample T. test and percentages statistical methods. Results of this study reveal that engineering students have great difficulties in reading comprehension since most of them have not succeeded in the test. Reasons behind such results have been illustrated and certain suggestions have been given to be useful for both teachers and students of scientific fields especially engineering.
In this article Silver nanoparticles have been synthesized through physical method where the Nd-YAG laser has been used.The antimicrobial activities of these silver nanoparticles were investigated on two types of bacteria Escherichia coli and Staphylococcus aureus. These bacteria were used as representatives of Gram-negative and Gram-positive bacteria, respectively. Two experiments have been made The first one was to test the effectiveness of silver nanoparticles as an antimicrobial agent on Gram negative bacteria Escherichia coli and Gram positive bacteria Staphylococcus aureus, while the other one (susceptibility Test) was to evaluate antimicrobial agents effective against bacteria resistant to multiple antibiotics. This study showed t
... Show MoreThe objective of this study is to investigate the application of advanced oxidation processes (AOPs) in the treatment of wastewater contaminated with furfural. The AOPs investigated is the homogeneous photo-Fenton (UV/H2O2/Fe+2) process. The experiments were conducted by using cylindrical stainless steel batch photo-reactor. The influence of different variables: initial concentration of H2O2 (300-1300mg/L), Fe+2(20-70mg/L), pH(2-7) and initial concentration of furfural (50-300 mg/L) and their relationship with the mineralization efficiency were studied.
Complete mineralization for the system UV/H2O2/Fe+2 was achieved at: initi
... Show MoreFour samples were collected from the wastewater of State Battery Manufacturing Company (SBMC); Babylon 2 factory in AL-Waziriya district, as triplicates. Physical and chemical measurements were carried out such as temperature, pH, Lead concentrations and their ranges were: (19.5-34.5) °C, (6.1-6.4) and (4.5-6.5) mg/L, respectively. Six dominant Bacillus spp. isolates were isolated from these samples; namely, Bacillus subtilis N1, Bacillus subtilis N2, Bacillus subtilis N3, Bacillus cereus N4, Bacillus cereus N5 , Bacillus cereus N6. These isolates were capable of removing Lead from aqueous solutions in a capacity reached 27.6 ± 1.4, 10.1 ± 1.7, 74.5 ± 0.7, 8.93 ± 2.8, 8.1 ± 3.5, 1.6± 0.7 mg/L, respectively. Whereas cell walls,
... Show MoreAttention-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
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