Objective: To assess the fear of laboring women regarding the delivery on themselves and their
newborns.
Methodology : A descriptive study was conducted on (100) pregnant women who where admitted to
labor room in Al- Yarmock Teaching Hospital/Maternity Units, Fatima Al- Zahra and Ibn-Al Baladi
Maternity and Pediatric Hospital. The questionnaire was consisted of pregnant women
socio-demographic data, reproductive data and fear items of labor. Data were collected by using a
questionnaire format, through interview technique and reviewing pregnant records, descriptive and
inferential statistical procedure were used to analyze the data.
Results: The main results of the study revealed a high mean of scores with moderate

Sustainability is a major demand and need pursued by cities in all areas of life due to the environmental, social and economic gains they provide, especially in the field of city planning and urban renewal projects that aim to integrate the past, present and future.

The research aims to evaluate the Haifa Street renewal project, and Al-Shawaka district, one of the Baghdad districts located next to Al-Karkh, was elected by comparing the sustainability indicators of urban renewal with the reality of the situation through a field survey and questionnaire form and focusing on the social and economic impacts and environmental for the project on the study area. To reach the most important conclusions and recommendations

Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as

Buildings such as malls, offices, airports and hospitals nowadays have become very complicated which increases the need for a solution that helps people to find their locations in these buildings. GPS or cell signals are commonly used for positioning in an outdoor environment and are not accurate in indoor environment. Smartphones are becoming a common presence in our daily life, also the existing infrastructure, the Wi-Fi access points, which is commonly available in most buildings, has motivated this work to build hybrid mechanism that combines the APs fingerprint together with smartphone barometer sensor readings, to accurately determine the user position inside building floor relative to well-known lan

The current study was designated to investigate the effect ofAllium sativumon some physiological and immunological parameters in rats. thirty adult rats were divided into three groups (10 rat for each). G1: served as healthy control, G2 :rats were treated with 150 mg\kg of Allium sativum, G3: treated with 300 mg\kg of Allium sativum. All treated animals were givenorally for 30 days. The aspartate , ) ALT ( alanine transaminase on some parameters were investigated such as garlic effects of total and differential counts of white blood , ) LDH ( lactate dehydrogenase ), AST ( transaminase cells(WBC) like Lymphocyte, Monocyte, Neutrophil, Basophil, Eosinophil,as

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Stool speeimens were collected from pati nts who presented for various medical c:omplaints  in out patien.t Laboratories (The Central Health  Laboratories  /  Baghdad,). Every ,$pecim-en  wa:s  examined  by Conventional   m jcroscopic  exatninatitnl  (CME) ·and  te.§t d,  by  IgG­ ELISA kit.

Antibody against d1e Entamoeba histolylica, det cted  by ELISA, has ·the potential  to  become a vah,mble adjunct  to blood diagn9stics and make it  more affective, .although there is no repJacement fo'e the

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      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate