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
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
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Background: Marginal adaptation is critical for long – term success of crown and bridge restoration. Computer aided design / computer aided manufacture (CAD/ CAM) system is gaining more importance in the fabrication of dental restoration. Objective: The aim of this study is to evaluate the effect of crystallization firing on the vertical marginal gap of IPS. emax CAD crowns which fabricated with two different CAD/CAM systems .Materials and Methods: Twenty IPS e.max CAD crowns were fabricated. We had two major groups (A, B) (10 crowns for each group) according to the CAD/CAM system being used: Group A: fabricated with Imes - Icore CAD/CAM system; Group B: fabricated with In Lab Sirona CAD/CAM system. Each group was subdivided into two s
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