Objectives of the study: Assess pregnant women's knowledge about tetanus toxoid vaccination, to find out the
relationship between pregnant women's knowledge and some variables which included: (age, level of
education, occupational status, socio-economic level, gravidity, parity, following visits of antenatal care,
tetanus toxoid vaccination coverage).
Methods and Materials: Descriptive analytic study conducted on multistage probabilistic sample of 130
pregnant women during period from 30th January 2012 to the 24th April 2013 was carried out in the six primary
health care centers at Karbala city. The questionnaire was consisted of four parts which include of: sociodemographic
characteristics, reproductive information, knowledge about tetanus toxoid vaccination, sources of
information regarding tetanus toxoid vaccine. Content validity and reliability of the questionnaire were
determined through pilot study, descriptive and inferential statistics were used to analyze the data.
Results: The results of the study showed that highest percentage (29.2%) of study sample were at age group
(20-24) years, (31.5%) of them were not read and write, and (97.7%) of them were housewives. The highest
percentage (68.5%) of them were living in low socio-economic level, the highest percentage (50.8%) of study
sample were had (2–4) pregnancies, and (40.8%) of them were had (2-4) deliveries, (72.3%) of them have
irregular visits to antenatal care, (76.2%) of them have partial vaccination coverage. Their knowledge were
adequate in some items ,and inadequate in other items, (72.3%) of them were not provided with information
about tetanus toxoid vaccine about it, (61.11%) of women that provided with information answered ; doctors
were source of their information. There were statistical significant association between level of knowledge and
(Level of education and Tetanus toxoid vaccination coverage) with probability value ≤ 0.05.
Recommendations: The study recommended to enhance women's knowledge on tetanus by using the various
mass media to increase the coverage of tetanus toxoid. Encouraging the pregnant women to have regular
antenatal care visits which consider the cause to contact with sources of tetanus toxoid and hence increase the
chance of vaccination.
Concrete columns with hollow-core sections find widespread application owing to their excellent structural efficiency and efficient material utilization. However, corrosion poses a challenge in concrete buildings with steel reinforcement. This paper explores the possibility of using glass fiber-reinforced polymer (GFRP) reinforcement as a non-corrosive and economically viable substitute for steel reinforcement in short square hollow concrete columns. Twelve hollow short columns were meticulously prepared in the laboratory experiments and subjected to pure axial compressive loads until failure. All columns featured a hollow square section with exterior dimensions of (180 × 180) mm and 900 mm height. The columns were categorized into
... Show MoreThe objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.
The database for this paper consists of night vision infrared images were taken by Zenmuse camera (FLIR Systems, Inc) attached on MATRIC100 drone in Karbala city. The experimental tests showed sign
Expanded use of antibiotics may increase the ability of pathogenic bacteria to develop antimicrobial resistance. Greater attention must be paid to applying more sustainable techniques for treating wastewater contaminated with antibiotics. Semiconductor photocatalytic processes have proven to be the most effective methods for the degradation of antibiotics. Thus, constructing durable and highly active photocatalytic hybrid materials for the photodegradation of antibiotic pollutants is challenging. Herein, FeTiO3/Fe-doped g-C3N4 (FTO/FCN) heterojunctions were designed with different FTO to FCN ratios by matching the energy level of semiconductors, thereby developing effective direct Z-type heterojunctions. The photodegradation behaviors of th
... Show MorePeriodontitis is a chronic inflammation affecting the tooth-supporting periodontal tissues. It is diagnosed by measuring periodontal parameters. However, documenting this data takes effort and may not discover early periodontitis. Biomarkers may help diagnose and assess periodontitis. This study aimed to evaluate the potential diagnostic of the salivary tumor necrosis factor-α (TNF-α) and receptor-activator of nuclear factor ĸ-B-ligand (RANKL) in distinguishing between periodontitis and healthy periodontium.
The
طريقة سهلة وبسيطة ودقيقة لتقدير السبروفلوكساسين في وجود السيفاليكسين او العكس بالعكس في خليط منهما. طبقت الطريقة المقترحة بطريقة الاضافة القياسية لنقطة بنجاح في تقدير السبروفلوكساسين بوجود السيفاليكسين كمتداخل عند الاطوال الموجية 240-272.3 نانوميتر وبتراكيز مختلفة من السبروفلوكساسين 4-18 مايكروغرام . مل-1 وكذلك تقدير السيفاليكسين بوجود السبروفلوكساسين الذي يتداخل باطوال موجية 262-285.7 نانوميتر وبتراكيز مخ
... Show MoreThe research included studying the effect of different plowing depths (10,20and30) cm and three angles of the disc harrows (18,20and25) when they were combined in one compound machine consisting of a triple plow and disc harrows tied within one structure. Draft force, fuel consumption, practical productivity, and resistance to soil penetration. The results indicated that the plowing depth and disc angle had a significant effect on all studied parameters. The results showed that when the plowing depth increased and the disc angle increased, leads to increased pull force ratio, fuel consumption, resistance to soil penetration, and reduce the machine practical productivity.
Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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