The aim: Infection with the hepatitis B virus (HBV) caused by blood transfusion is a big problem throughout the world. The aim of study is to determine the faster and more accurate methods for detection of hepatitis B infections by serological screening and PCR- amplification. Materials and methods: A total of 140528 donors were tested for HBsAg and total anti-HBc from January to October 2021 in Iraq’s National Blood Transfusion Center; however, only 100 samples with HBsAg (-) and anti-HBc (+) were collected and tested for HBV DNA using quantitative real-time PCR. Results: From 2015 to 2021, the percentage of HBsAg positive donors was 0.33 percent in 2015, 0.32 percent in 2016, 0.30 percent in 2017, 0.28 percent in 2018, 0.23 pe

Background: Molars and premolars are considered as the most vulnerable teeth of caries attack, which is related to the morphology of their occlusal surfaces along with the difficulty of plaque removal. different methods were used for early caries detection that provide sensitive, accurate preoperative diagnosis of caries depths to establish adequate preventive measures and avoid premature tooth treatment by restoration. The aim of the present study was to evaluate the clinical sensitivity and specificity rates of DIAGNOdent and visual inspection as opposed to the ICDAS for the detection of initial occlusal caries in noncavitated first permanent molars. Materials and Methods: This study examined 139 occlusal surface of the first permanent

Attention-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

    A survey conducted at Dalmaj marsh, Al-Diwaniya Province during 2013 revealed that the marsh encounters a considerable part of the Iraqi vertebrate fauna including 147 species belonging to five classes; Pisces, Amphibia, Reptilia, Aves and Mammalia. Some species are of globally conservation importance. The present results are discussed with the pertinent literature.

Despite the significant increase in women in academic medicine over the last 50 years, women are still under-represented in leadership positions in academia. However, there is a lack of data on the diversity of editorial boards in Middle Eastern medical journals. So, we aim to portray the diversity of editorial boards of Iraqi medical journals by conducting a cross-sectional analysis of the editorial boards’ members of all Iraqi medical journals. Gender, affiliation and specialty were extracted from the journals’ websites and/or from the professional profiles of the editorial board members. Twenty-five journals and 446 editorial board members were analysed. More than half of editorial board members specialized in basic scienc

In the digital age, protecting intellectual property and sensitive information against unauthorized access is of paramount importance. While encryption helps keep data private and steganography hides the fact that data are present, using both together makes the security much stronger. This paper introduces a new way to hide encrypted text inside color images by integrating discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD), along with AES-GCM encryption, to guarantee data integrity and authenticity. The proposed method operates in the YCbCr color space, targeting the luminance (Y) channel to preserve perceptual quality. Embedding is performed within the HL subband obtained from DWT deco

Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect