Objective)s): To evaluate the quality of life for adult clients with hypermobility syndrome at private clinics in Baghdad City. Methodology: A cross-sectional study used a purposive ‘’non-probability’’ sample of (75) adult clients with Hypermobility Syndrome (HMS) male and female who age (25-64) years. The data were collected through the utilization of standard developed questionnaire of the world health organization (WHO). Data collected by interview with each client who is involved in the study. Each interview takes approximately (20) minutes. Results: The study revealed that there is an effect of hypermobility syndrome on the quality of life, which recorded fair level in general. The study also reported that there is an effect of the condition on their physical, social and psychological domains. Recommendation: The study recommends that early diagnosis of hypermobility syndrome is essential to recognize and increase knowledge about condition for clients and their families, and that consultation and health education programs can help to prevent and minimize symptoms and raise the level of quality of life.
A sensitivity-turbidimetric method at (0-180o) was used for detn. of mebeverine in drugs by two solar cell and six source with C.F.I.A.. The method was based on the formation of ion pair for the pinkish banana color precipitate by the reaction of Mebeverine hydrochloride with Phosphotungstic acid. Turbidity was measured via the reflection of incident light that collides on the surface particles of precipitated at 0-180o. All variables were optimized. The linearity ranged of Mebeverine hydrochloride was 0.05-12.5mmol.L-1, the L.D. (S/N= 3)(3SB) was 521.92 ng/sample depending on dilution for the minimum concentration , with correlation coefficient r = 0.9966while was R.S.D%
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
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The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat
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: zonal are included in phraseological units, form metaphorical names for a person, give him various emotional and evaluative characteristics. This article examines the topic of zoomorphic metaphors that characterize a person in the Russian and Arabic languages in the aspect of their comparative analysis, since the comparative analysis of the metaphorical meanings of animalisms is an important method for studying cultural linguistics, since zoomorphic metaphors are a reflection of culture in a language.
This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota
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