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
Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
... Show MoreThe spectrum of clinical efficacy of Methotrexate (MTX) is broad in that MTX is used in the treatment of certain cancers, severe psoriasis and rheumatoid arthritis.Various mechanisms by which cancer cells grown in tissue culture become resistant to anticancer drugs. The use of multiple drugs with different mechanisms of entry into cells and different cellular targets allows for effective chemotherapy and high cure rates. In an efforts to develop effective strategies that increase the therapeutic potential of anticancer drugs with less systemic toxicity ,are being directed towards the investigation of dietary supplements and other phytotherapeutic agents for their synergistic efficacy in combination with anticancer drugs. A promi
... Show MoreClassifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area. The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and
... Show MoreIn this work Nano crystalline (Cu2S) thin films pure and doped 3% Al with a thickness of 400±20 nm was precipitated by thermic steaming technicality on glass substrate beneath a vacuum of ~ 2 × 10− 6 mbar at R.T to survey the influence of doping and annealing after doping at 573 K for one hour on its structural, electrical and visual properties. Structural properties of these movies are attainment using X-ray variation (XRD) which showed Cu2S phase with polycrystalline in nature and forming hexagonal temple ,with the distinguish trend along the (220) grade, varying crystallites size from (42.1-62.06) nm after doping and annealing. AFM investigations of these films show that increase average grain size from 105.05 nm to 146.54 nm
... Show MoreTo ensure that a software/hardware product is of sufficient quality and functionality, it is essential to conduct thorough testing and evaluations of the numerous individual software components that make up the application. Many different approaches exist for testing software, including combinatorial testing and covering arrays. Because of the difficulty of dealing with difficulties like a two-way combinatorial explosion, this brings up yet another problem: time. Using client-server architectures, this research introduces a parallel implementation of the TWGH algorithm. Many studies have been conducted to demonstrate the efficiency of this technique. The findings of this experiment were used to determine the increase in speed and co
... Show MoreThe recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med
... Show MoreMCM-48 zeolites have unique properties from the surfaces and structure point of view as it’s shown in the results ,and unique and very sensitive to be prepared, have been experimentally prepared and utilized as a second-generation/ acid - catalyst for esterification reactions of oleic acid as a model oil for a free fatty acid source with Ethanol. The characterization of the catalyst used in the reaction has been identified by various methods indicating the prepared MCM-48 is highly matching the profile of common commercial MCM-48 zeolite. The XRF results show domination of SiO2 on the chemical structure with 99.1% and agreeable with the expected from MCM-48 for it's of silica-based, and the SEM results show the cubic c
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