The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of Deep Bayesian Neural Network (DBNN) for the personalized treatment of leukemia cancer has shown a significant tested accuracy for the model. DBNNs used in this study was able to classify images with accuracy exceeding 98.73%. This study depicts that the DBNN can classify cell cultures only based on unstained light microscope images which allow their further use. Therefore, building a bayesian‐based model to great help during commercial cell culturing, and possibly a first step in the process of creating an automated/semiautomated neural network‐based model for classification of good and bad quality cultures when images of such will be available.
The study was carried out to detection of H.pylori in (200) patients who attended two teaching hospitals in Baghdad. The diagnosis done by Immunochromatography methods. Stools and blood samples was taken from each patient as well as other (30) healthy control matching in their age. The study included detection the Levels of Interleukin-40 and CRP in sera of patients and control. The result indicated presence of H pylori antigen in 115 cases 59 cases of males and 51 of females, Also, the result indicated increasing levels of IL-40, cholesterol, Triglycerides, Low density lipoprotein, Very Low density lipoprotein increased significantly while the level of High density lipoprotein decreased in patients sera in comparison with healthy c
... Show Moreتحقق القراءةُ التَّناصيَّة قيمة موضوعيَّة للدرسِ النَّقديّ المعاصر؛ بمؤثراتها الثَّقافيَّة، والمعرفيَّة، لأنَّ الإبداعَ من سمات التُّراث الشِّعري في العصر الوسيط، وهو مسرحٌ لتداخلات نصِّيَّة مع مصادر متعددة دينيَّة، وأدبيَّة، وتاريخيَّة أداء ومضامين؛ يأتي اختيارُ (التَّناص مع الحديث النَّبوي في شعر صفيّ الدِّين الحلّي)؛ بوصفه امتدادًا شعريَّا أصيلًا لحضارة راقية معطاء
... Show MoreThis study aimed to show the histological changes that 0ccured in Culex pipiens pipiens larvae and adults infected with Beauveria bassiana . The 4th instar larvae and adult mosquitoes were infected with B.bassiana in 10-4 spore/ml dilution, after 96 hours histological section was studied showing that the fungi infected all the body parts specially Cuticle , Epiderms, fat bodies and midgut. After 120 hours of exposure to the fungi the insect have a white appearance and covered with a thick coat of hyphea. Thus study shows biological control of B .bassiana on mosquitoes.
The dramatic series on television have a great impact on people’sattitudes towards dialects of language varieties, by relating theconceptual pictures or prototypes presented by series’ characters tothose dialects. This study aims to show the influence of TV series onIraqi university learners’ gender and age in relating positive ornegative semantic qualities to their dialects. To this end, 150 Iraqi EFLlearners have participated in this study to examine their attitudestowards Baghdadi, Mousli and Nasiriya dialects. The data arecollected by Lambert, Hodgson, Gardner, Fillenbaum's (1960)matched guise technique and then labeled by Willmorth’s (1988)subjective reaction test. A structured interview is conducted to supportthe data
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThe analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the
... Show MorePrevious studies on the synthesis and characterization of metal chelates with uracil by elemental analysis, conductivity, IR, UV-Vis, NMR spectroscopy, and thermal analysis were covered in this review article. Reviewing these studies, we found that uracil can be coordinated through the electron pair on the N1, N3, O2, or O4 atoms. If the uracil was a mono-dentate ligand, it will be coordinated by one of the following atoms: N1, N3 or O2. But if the uracil was bi-dentate ligand, it will be coordinated by atoms N1 and O2, N3 and O2 or N3 and O4. However, when uracil forms complexes in the form of polymers, coordination occurs through the following atoms: N1 and N3 or N1 and O4.