Objectives: The study aims to (1) Assess the parents' efficacy for child healthy weight behavior. (2) Identify the difference in parents’ efficacy for child healthy weight behavior between the groups of parent’s gender, family’s socioeconomic status, child’s gender, and child’s birth order, (3) Find out the relationship between parents’ age, child’s age, child’s body mass index, family’s socioeconomic status, the number of children in the family and parents’ efficacy for child healthy weight behavior.
Methodology: A descriptive correlational study is conducted for the period from November 11th, 2018 to March 25th, 2019 to assess the parents' efficacy for child healthy weight behavior. The study was carried-out in (30) primary schools that were selected through a simple random sampling of (125) schools from Hilla City. The instruments was composed of two parts , the first part was the demographic data and the second part was the Parent Efficacy for Child Healthy Weight Behavior (PECHWB) Scale, it consists of 41 items based on Australian guidelines for healthy weight behaviors. The validity of the instrument was achieved by eleven experts. Data were collected for the period from January 10th to March 5th, 2019. Data were analyzed using the statistical package for social sciences (SPSS) version 24.
Results: The study results revealed that most of pupils eat three or more serves of fruit and vegetables per day, minimize high fats and sugar intake, engaging in one hour of physical activity per day, and being no more than two hours in sedentary behavior per day on holidays/vacations and on weekends. Furthermore, they minimize high fats and sugar intake and eat healthy snacks on their demands/request. Moreover, they do not minimize high fats and sugar intake and eat healthy snacks when they are stressed or in bad mood and when they complain.
Recommendations: The researcher recommends establishing health activities that aim to raise the public’s awareness of fostering healthy lifestyle and behaviors for their children
Increasing the power conversion efficiency (PCE) of silicon solar cells by improving their junction properties or minimizing light reflection losses remains a major challenge. Extensive studies were carried out in order to develop an effective antireflection coating for monocrystalline solar cells. Here we report on the preparation of a nanostructured cerium oxide thin film by pulsed laser deposition (PLD) as an antireflection coating for silicon solar cell. The structural, optical, and electrical properties of a cerium oxide nanostructure film are investigated as a function of the number of laser pulses. The X-ray diffraction results reveal that the deposited cerium oxide films are crystalline in nature and have a cubic fluorite. The field
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This study investigates the application of hydraulic acid fracturing to enhance oil production in the Mishrif Formation of the Al-Fakkah oilfield due to declining flow rates and wellhead pressures resulting from asphaltene deposition and inadequate permeability. Implementing acid fracturing, an established technique for low-permeability carbonate reserves, was essential due to the inadequacy of prior solvent cleaning and acidizing efforts. The document outlines the protocols established prior to and following the treatment, emphasizing the importance of careful oversight to guarantee safety and efficacy. In the MiniFrac treatment, 150 barrels of #30 cross-linked gel were injected at 25 barrels per minute, followed by an overflush wi
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The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences
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This paper predicts the resilient modulus (Mr) for warm mix asphalt (WMA) mixtures prepared using aspha-min. Various predictor variables were analyzed, including asphalt cement types, asphalt contents, nominal maximum aggregate sizes (NMAS), filler content, test temperatures, and loading times. Univariate and multivariate analyses were conducted to examine the behavior of each predictor variable individually and collectively. Through univariate analysis, it was observed that Mr exhibited an inverse trend with asphalt cement grade, NMAS, test temperature, and load duration. Although Mr increased slightly with higher filler and asphalt content, the magnitude of this increase was minimal. Multivariate analysis revealed that the rate of change
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In this study, gold nanoparticles were synthesized in a single step biosynthetic method using aqueous leaves extract of thymus vulgaris L. It acts as a reducing and capping agent. The characterizations of nanoparticles were carried out using UV-Visible spectra, X-ray diffraction (XRD) and FTIR. The surface plasmon resonance of the as-prepared gold nanoparticles (GNPs) showed the surface plasmon resonance centered at 550[Formula: see text]nm. The XRD pattern showed that the strong four intense peaks indicated the crystalline nature and the face centered cubic structure of the gold nanoparticles. The average crystallite size of the AuNPs was 14.93[Formula: see text]nm. Field emission scanning electron microscope (FESEM) was used to s
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Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.
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