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

Background: Community pharmacists endure significantly elevated levels of work-related stress and depression, posing a threat to their overall well-being and possibly affecting the quality of patient care. Objectives: To explore workplace-associated stress and depression in Iraqi community pharmacists. Methods: This observational study was conducted using a cross-sectional design. Information was gathered through the utilization of an internet-based survey. The study involved a community pharmacist with a minimum of one year of experience working at community pharmacies. The survey utilized pre-validated questionnaires. The level of stress experienced was assessed using the Perceived Stress Scale (PSS)-10, while the level of depression was

Objective: This study aimed to explore the social and physiological changes that Iraqi women may experience after a hysterectomy.                                       Methods: A cross-sectional study was conducted at the consultation clinic of Al-Elwiya Maternity Teaching Hospital in Baghdad, Iraq. A total of 81 women who underwent emergency hysterectomy and could comprehend and respond to the questionnaire were recruited for this study. A structured, self-administered Arabic-language questionnaire was developed, and it included sociodemographic characteristics, surgical history, preoperative awareness, psychological symptoms, and sexual health impact. Results: The mean age of patients was 43.5

The Reversed Phase High Performance Liquid Chromatography (RP-HPLC) has been used for the separation of Poly aromatic hydrocarbons(PAHs) by using column Reprosil 100 C 18 which was found to be a suitable one for this purpose. The result showed that using mobile phase of (Acetonitrile-water) Reversed Phase HPLC , flow rate of (1.2 ml/min) , column temperature (30CËš) and wave length of (254nm), give a complete separation with a good resolution . The total separation time was less than 20 min. The result of the study showed that the vegetables of Baghdad city were polluted by poly aromatic hydrocarbons(PAHs) in different places where samples taken because of drainage of the heavy water ,industrial trash and trash of oil colanders. -

Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysi