Chronic lymphocytic leukaemia (CLL) patients display a highly variable clinical course, with progressive acquisition of drug resistance. We sought to identify aberrant epigenetic traits that are enriched following exposure to treatment that could impact patient response to therapy.

    The electronic properties (such as energy gap HOMO levels. LUMO levels, density of state and density of bonds in addition to spectroscopic properties like IR spectra, Raman spectra, force constant and reduced masses as a function of frequency) of coronene C24 and reduced graphene oxide C24OX , where x=1-5, were studied.. The  methodology employed was  Density Functional Theory (DFT) with Hybrid function B3LYP and 6-311G** basis sets. The energy gap was calculated for C24 to be 3.5 eV and for C24Ox was from 0.89 to 1.6862 eV  for x=1-5 ,respectively.   These energy gaps values are comparable to the measured gap of Graphene (1-2.2 eV). The spectroscopic properties were  compared with experimental measurements, specificall

Abstract

This Research aims for harnessing critical and innovative thinking approaches besides innovative problem solving tools in pursuing continual quality improvement initiatives for the benefit of achieving operations results effectively in water treatment plants in Baghdad Water Authority. Case study has been used in fulfilling this research in the sadr city water treatment plant, which was chosen as a study sample as it facilitates describing and analyzing its current operational situation, collecting and analyzing its own data, in order to get its own desired improvement opportunity be done. Many statistical means and visual thinking promoting methods has been used to fulfill research task.

Objective(s): To evaluate the family physicians' practices and to measure its impact upon the quality of family
medicine health care in Baghdad City model primary health care centers.
Methodology: A descriptive study, using the evaluation approach, has evaluated the impact of family physicians'
practices upon quality of healthcare in Baghdad's Model Primary Health Care Centers of Family Medicine. It is
carried out during 15th of May – 20th of August 2017. The study is conducted at five model primary health care
centers of family medicine from two districts; AL-Rusafa and AL-Kurkh. Sample size is calculated to be (76)
family physicians. Convenient sample of (124) patients who are attending these primary health care cen

This investigation presents an experimental and analytical study on the behavior of reinforced concrete deep beams before and after repair. The original beams were first loaded under two points load up to failure, then, repaired by epoxy resin and tested again. Three of the test beams contains shear reinforcement and the other two beams have no shear reinforcement. The main variable in these beams was the percentage of longitudinal steel reinforcement (0, 0.707, 1.061, and 1.414%). The main objective of this research is to investigate the possibility of restoring the full load carrying capacity of the reinforced concrete deep beam with and without shear reinforcement by using epoxy resin as the material of repair. All be

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark