Background: breast cancer is commonest cancer globally and the 1st cancer in Iraq among females, its management and prognosis depend on early diagnosis, the traditional method was excisional biopsy which is expensive and invasive leading to delayed diagnosis, FNAB is cheap nom invasive more acceptable to women, Aim of the study: to test the reliability of FNAB in preoperative diagnosis of breast lump.

Methodology: This is a retrospective study of 204 cases, 102 breast cancer cases and 102 benign breast lesions, taken between Jan. 2017 – Nov. 2017. The sample taken from the breast cancer early detection center in  Al-Alwiyaa maternity teaching hospital, during the year 2017

Background: Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is one of the most common infectious diseases, especially in countries with limited healthcare resources. Early and accurate diagnosis is essential to curb its spread, and loop-mediated isothermal amplification (LAMP) is a rapid, cost-effective, and reliable molecular diagnostic method. Objective: The objective of this study was to evaluate the performance of TB-LAMP as a rapid and reliable diagnostic tool for pulmonary TB and compare it with direct smears and Gene Xpert, using culture as a reference. Materials: Between February and July 2025, a total of 397

Objective: To determine the prevalence of bullying among primary schools’ children with some associated factors, and resultant effects. Methodology: This cross-sectional study with analytic elements was carried out from February through April 2022. It included a sample of 410 students from six governmental primary schools from both sides of Baghdad city. A self-constructed questionnaire was used. It comprised the following parts: Part (1): socio-demographic data, Part (2): questions that review the students’ exposure to bullying, and Part (3) entails the effects of bullying on those children. Results: The total sample was composed of 410 students; their mean age was 9.51±1.94 years. The prevalence of bullying was 56.34%. Studen

Abstract  

This research aims to study and improve the passivating specifications of rubber resistant to  vibration. In this paper, seven different rubber recipes were prepared based on mixtures of natural rubber(NR)  as an essential part in addition to the synthetic rubber (IIR, BR_cis, SBR, CR)with different rates. Mechanical tests such as tensile strength, hardness, friction, resistance to compression, fatigue and creep testing in addition to the rheological test were performed. Furthermore, scanning electron microscopy (SEM)test was used to examine the structure morphology of rubber. After studying and analyzing the results, we found that, recipe containing (BRcis) of 40% from th

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

ملامح من فكرة القانون الطبيعي في حضارة العراق القديم

The insects like other creatures in the wide world, and there are more than a million class and type of these objects, some of which human haunted since the old to the present day.

 In this study highlight the insect bee addressing her life and behavior, and the novelty of her and wonders what mystified by the minds of men that her world is full of mysteries and surprises drew the attention of workers in the natural history of the study and scrutiny of methods and different characteristics of scientists as she gives more than it takes. It appeared that the Islamic heritage has singled out these insects with something of interest and precise detail, but that God Almighty made suras from the Koran carrying insect name two Sura

Myocardial infarction (MI) is a prevalent disease and is expected to become the main cause of death globally in the future The pathophysiology of MI is tightly linked to the activation of the NLRP3 inflammasome. This study involves 60 subjects who were enrolled in the Intensive Care Unit (ICU) at Ibn Al-Bitar Center for Cardiac Surgery. Patients admitted to the ICU at Baghdad Teaching Hospital and Ibn Al-Bitar Cardiac Surgery Center were included in this study, conducted from November 26, 2023, to November 20, 2024. The control group also consisted of 60 subjects, In this study ,uric acid , urea , creatinine ,Glutamic Pyruvic Transaminase (GPT) Glutamic Oxaloacetic transaminase (GOT) , Gamma Glutamyl Transferase (GGT) ,NLPR3, NT-pro

Colloidal silver nanoparticles were prepared by single step green synthesis using aqueous extracts of the leaves of thyme as a function of different molar concentration of AgNO₃ (1,2,3,4 mM(. The Field Emission Scanning Electron Microscopy (FESEM), UV-Visible and X-ray diffraction (XRD) were used to characterize the resultant AgNPs. The surface Plasmon resonance was observed at wavelength of 444 nm. The four intensive peaks of XRD pattern indicate the crystalline nature and the face centered cubic structure of the AgNPs. The average crystallite size of the AgNPs ranged from 18 to 22 nm. The FESEM image illustrated the well dispersion of the AgNPs and the spherical shape of the nanoparticles with a particle size distribution be

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration