Objective: The study aims at assessing the food frequency intake and dietary habits for diabetic pregnant
women.
Methodology: A descriptive study is carried out for the period from November4th 2013 to August
25th 2014. A purposive "non-probability" sample of one hundred diabetic pregnant women is selected from
the Diabetic and Endocrine Center in Al-Amarha City. A questionnaire is developed as a tool of data
collection. Content validity of the study instrument is determined through panel of experts. Split-half
reliability technique is used for reliability determination of the study instrument which depicts a reliability
coefficient of (0.79) for the entire scale. A structured interview with each diabetic pregnant woman is
applied for data collection. Data are analyzed through the application of descriptive statistical data analysis
approach of frequency, percent and standard deviation and inferential statistical data analysis approach of
linear regression.
Results: The results of the study indicated that the vast majority of pregnant women have acceptable level
of food frequency intake and dietary habits. Being them pregnant with diabetes, they need to have more
than acceptable level so they can go through a healthy and safe pregnancy, as well as labor and having a
healthy baby without complications.
Recommendations: The study recommends for the initiation of collaboration and coordination between
the Nutrition Research Institute and the Diabetic and Endocrine Center in Al-Amara City concerning the
diabetic pregnant women and their dietary patterns. Further study can be conducted on a large sample size
and nation-wide base.
Most available methods for unit hydrographs (SUH) derivation involve manual, subjective fitting of
a hydrograph through a few data points. The use of probability distributions for the derivation of synthetic
hydrographs had received much attention because of its similarity with unit hydrograph properties. In this
paper, the use of two flexible probability distributions is presented. For each distribution the unknown
parameters were derived in terms of the time to peak(tp), and the peak discharge(Qp). A simple Matlab
program is prepared for calculating these parameters and their validity was checked using comparison
with field data. Application to field data shows that the gamma and lognormal distributions had fit well.<
Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance
... Show MoreThe objective of this research was to estimate the dose distribution delivered by radioactive gold nanoparticles (198 AuNPs or 199 AuNPs) to the tumor inside the human prostate as well as to normal tissues surrounding the tumor using the Monte-Carlo N-Particle code (MCNP-6.1. 1 code). Background Radioactive gold nanoparticles are emerging as promising agents for cancer therapy and are being investigated to treat prostate cancer in animals. In order to use them as a new therapeutic modality to treat human prostate cancer, accurate radiation dosimetry simulations are required to estimate the energy deposition in the tumor and surrounding tissue and to establish the course of therapy for the patient. Materials and methods A simple geometrical
... Show MoreThe new azo dye was prepared from the reaction of the diazonium salt derived from 3-aminophenol with 2- hydroxyquinoline, then it was used to prepare a series of complexes with the chlorides of cobalt, chromium, copper, nickel, platinum, palladium and ammonium molybdate. The ligand was identified by a proton and carbon nuclear magnetic resonance spectroscopy, and the compounds were collected. The prepared materials were subjected to infrared, ultraviolet-visible, and mass spectrometry, as well as thermogravimetric analysis, differential calorimetry, and elemental analysis. Conductivity, magnetic susceptibility, metal content, and chlorine content of the complexes were also measured. The results showed that the ligand behaves in a trigonal b
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