Over the past few decades, the global usage and applications of different kinds of complementary and alternative medicine are greatly exaggerated among the general population, this requires improving the knowledge of all health care provider including pharmacists toward proper and safe use of different complementary and alternative medicine modalities. The current study aims to assess the Iraqi pharmacists' knowledge, use, and recommendation toward complementary and alternative medicine A cross-sectional pilot survey was done on a convenient sample of Iraqi pharmacists. Data were collected using a pretested 

Objective: To assess the nurses-midwives' knowledge and practices regarding the management of second stage
of labor and to find out the association between their knowledge and practices and socio-demographic
characteristics and working years and experience.
Methodology: A descriptive study was carried out from March 22nd
, 2008 through 30th June, 2008. A purposive
sample of (75) Nurse-Midwives which was selected from (6) hospitals. A questionnaire was comprised of two
parts: (socio-demographic characteristics and the assessment tool for Nurse-Midwives' knowledge and health
practices performed by them). The questionnaire validity was determined by experts and its reliability was
determined through a pilot study. Th

To assess the total hip replacement patients’ knowledge of home – care regarding pain management, medication therapy, wound care, mobility limitation and complications may occur in the post hip replacement surgery, and to assess relationship between some variables such as, age level of education, sex & marital status with home- care knowledge. A descriptive study was used to assess the hip-replacement patient home-knowledge, a purposive sampling of (60) hip-replaced –patients were selected from Gazy Alhariri Hospital  (central of surgical profession ) and Alwasity Hospital ( plastic surgery) , the questionnaire  obtains two parts , part one, which included socio-demographical characteristics of the samp

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

Recently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in

The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca

Terahertz (THz) technology, which uses radiation lying between microwave and infrared in the electromagnetic spectrum, could revolutionize digital agriculture through terahertz’s ability to assess agricultural materials accurately and non-destructively. The review discusses notable developments in THz applications to digital agriculture: real-time crop monitoring, nutrient and disease detection, soil moisture and contaminant analysis, and supply chain traceability. The developments have emerged from studies in time-domain spectroscopy, imaging, machine learning (ML), and blockchain integration. Despite the promising advances in THz agricultural applications, limitations remain, such as limited penetration depth, high system costs, and ope

Background: Infections are common in the children attending daycare centers how act as predisposes to it. Hygienic interventions have a fundamental role in infection control and disease prevention in child care settings.

Objective: - To evaluate the knowledge, attitude, and practice of nurseries workers in infection prevention and control among the children.

Subjects and Methods: A cross-sectional study using the researcher-developed questionnaire validated by two experts and piloted and 100 nurseries-workers had participated in it.

Result: the mean age of participants was 37.5 years±12.1, (37%) aged 18-30 yrs, 58% married, and 57% with higher education, 54% of n

Objective(s): To evaluate nurses’ Practice toward neonatal endotracheal suctioning procedure, and to determine the effectiveness of the interventional program on nurses’ practices, as well as to find out the relationship between nurses’ practice and their demographic characteristics.

Methodology: A Pre-experimental, one group design, was carried out to achieve the objectives of the current study using the evaluation approach and the implementation of the education program for the period from January 17 to June 31, 2022. A non- probability, purposive sample of (24) nurses were selected from the Neonatal Intensive Care Unit at Pediatric Teaching Hospital/ Medical City Department. A checklist w