Abstract:
The research aimed to know favoured mass media for children and
modifying their behaviour ,the child became aquires the information from
mass media that he exposure them without any guidance , where upon the
quidance proqrammes becomes real danger whereas qet out their civil

style and converting to deadly poisons,and because of little study for this
supject the two researchers opined to perform astudy to know the favoured
mass media to the children and what are the mass media that modify their
behavior according to ther parent points of view ,after propring the research
measurement and the suilable statical methods it has shown that there are
mass media affect in children behavior ,they are st

AlPO4 catalysts supported with WO3 were prepared by impregnating the catalysts with ammonium metatungstate. The catalysts were checked by X-ray Diffraction (XRD), AFM, and SEM; also, the catalysts analysis was done by X-Ray (EDX). Finally, the N2 adsorption-desorption was used to measure the pore volume and surface area of the catalyst. The prepared catalyst has a surface area of 185.83 m2/g, pore volume of 0.645 cm3/g at a calcination temperature of 500°C for 3 hrs, and particle size of AlPO4 with an average of 35.36 nm. Transesterification of edible oil using WO3/AlPO4 was performed, it was observed that WO3/AlPO4 catalysts give high conversion of edible oil, and this is attributed to the high surface area, smaller particle size, and the

The UN plans to achieve several development objectives by 2030. These objectives address global warming, a major issue. This method aims to improve sustainable accounting performance (AP). In this circumstance, AI is being applied in various fields, notably in economic, social, and environmental (ESE) domains. This research investigates how sustainable development (SD) influences AI methodologies and AP improvement. The research examined a sample of Iraqi banks listed on the Iraq Stock Exchange from 2014 to 2022. AI was measured by ATM and POS prevalence. A three-dimensional approach examined economic, social, and environmental (ESE) sustainability. Meanwhile, the performance of sustainable accounting was measured through the return on asse

Shumblan (SH) is one of the most undesirable aquatic plants widespread in the irrigation channels and water bodies. This work focuses on boosting the biogas potential of shumblan by co-digesting it with other types of wastes without employing any chemical or thermal pretreatments as done in previous studies. A maximum biogas recovery of 378 ml/g VS was reached using shumblan with cow manure as inoculum in a ratio of 1:1. The methane content of the biogas was 55%. Based on volatile solid (VS) and C/N ratios, biogas productions of 518, 434, and 580 ml/g VS were obtained when the shumblan was co-digested with food wastes (SH:F), paper wastes (SH:P), and green wastes (SH:G) respectively. No significant changes of methane contents were observ

The total and individual multipole moments of  magnetic electron scattering form factors in ⁴¹Ca  have been investigated using a widely successful model which is the nuclear shell model configurations keeping in mind of 1f_7/2 subshell as an L-S shell and Millinar, Baymann, Zamick as L-S shell (F7MBZ) to give the model space  wave vector. Also, harmonic oscillator wave functions have been used as wave function of a single particle in 1f_7/2  shell. Nucleus ⁴⁰Ca as core closed and Core polarization effects have been used as a corrective with first order correction concept to basic computation of L-S shell and the excitement energy has been implemented with 2ћω. The

Background: Irrigation has a central role in endodontic treatment. Several irrigating solutions have the antimicrobial activity and actively kill bacteria and yeasts when introduced in direct contact with the microorganisms. The purpose of this study was to evaluate the antimicrobial effectiveness of Dandelion (Taraxacum officinale) root and leaf extracts as possible irrigant solutions, used during endodontic treatments, and both were compared to Sodium hypochlorite, Propolis and Ethyl alcohol. Materials and Method: Forty seven human extracted single rooted teeth were selected. The teeth were decoronated using a diamond disk to have a length of 15 mm ±1 mm and they were instrumented using the hybrid technique. All roots were sterilized

The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca

The present study tackles the complex issue of the urgent need for Environmental Auditing (EA) in Iraq in the absence of laws that support environmental management and in the light of the high rates of cancerous diseases in Iraq, which coincided significantly with the increase in oil production, according to the numbers indicated in the Iraqi Ministry of Health. The study aimed to investigate the mediating role of Management Systems (MS) related to the role of EA supporting sustainability reports concerning the reduction of the negative effects of gas emissions from oil companies. We adopted the descriptive approach which relies on studying relationships through a questionnaire that was distributed to a group of workers at Doura Refinery in

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification