Back ground : Fever is a common medical problem in
children. parents have been shown unrealistic fears of
harmful effects of fever in their children. Resulting in
inappropriate management of fever in their children.
Objective: the objective of this study was to survey
parents about their knowledge andattitude concerning fever
in their children.
Methods : The study involved random selection of
parents who brought their febrile children to emergency
department or out-patient clinics of five teaching and non
teaching hospitals in Baghdad from first of October to end
of December 2002.
Parents of 400 febrile children were interviewed using a
standard questionnaire to obtain sociodemographic
information and current knowledge of fever.
Results: Approximately 69% of the respondents were
female, 68% their age was in the range of 21-35 years.
Seventy seven percent of parents had two or more children.
More than 70% of parents demonstrated a poor
understanding of definition of fever , maximum
temperature of untreated fever and threshold temperature
requiring antipyretics . Twenty sevev percent of parents
considered temperature less than 38.0 c
o
to be fever,
another 27% did not know, the definition of fever, 61% felt
that temperature of less than 40,0 c
o
could be dangerous to
a child, and 27% could not define high fever. Another 28%
believed that if left untreated, temperature could rise to
42.0 c
o
or higher, but 39% could not provide an answer,
and about 60% did not know the minimum temperature for
administering antipyretics. And 60% did not know the
minimum temperature for bathing , or sponging.
Approximately 93% of parents demonstrated fear of
consequent body damage from fever , including convulsion
,brain damage ,coma, blindness and even death.
Conclusion: parental misconception about fever reflects
the lack of active health education. Health professionals
have apparently not done enough to educate parents on this
common medical problem and it,
s consequences
A political perusal of Initiations in Declaring Middle East a District vacant of mass Destruction weapons
It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i
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Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec
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The last decade has seen a variety of modifications of glass-ionomer cements (GICs), such as inclusion of bioactive glass particles and dispensing systems. Hence, the aim was to systematically evaluate effect of mixing modes and presence of reactive glass additives on the physical properties of several GICs.
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