Artificial intelligence (AI) offers significant benefits to biomedical research and academic writing. Nevertheless, using AI-powered writing aid tools has prompted worries about excessive dependence on these tools and their possible influence on writing proficiency. The current study aimed to explore the academic staff’s perspectives on the impact of AI on academic writing. This qualitative study incorporated in-person interviews with academic faculty members. The interviews were conducted in a semi-structured manner, using a predetermined interview guide consisting of open-ended questions. The interviews were done in person with the participants from May to November 2023. The data was analyzed using thematic analysis. Ten academics aged 41 to 59 years participated in this study. The majority had assistant professor degrees. Most of the participants did not trust the ability of AI to write an accurate scientific article because it can provide inaccurate results and/or improper citations. Regarding the concerns about the usage of AI in academic writing, most participants had negative perceptions, and they believed that AI would diminish students' writing skills. Most participants reported the impossibility of AI being the sole author of scientific articles; instead, it can just support humans in academic writing. Students could use AI to obtain scientific information, get some research ideas, improve writing by reducing grammatical errors, and save students time in writing. To get benefits from AI in academic writing, The faculty members agreed on the necessity of issuing legislation about the usage of AI by the Ministry of Higher Education or the University. Additionally, all agreed on the necessity of conducting workshops to teach staff about AI. Finally, we can conclude that AI could potentially play a beneficial role in academic writing. However, most academic faculty express concerns about their students relying only on these tools, which may result in dependency and a decline in writing proficiency. It is crucial to develop regulations and conduct workshops to educate staff about AI and its utilization by the Ministry of Higher Education or the University.
Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate
... Show MoreThis study offers numerical simulation results using the ABAQUS/CAE version 2019 finite element computer application to examine the performance, and residual strength of eight recycle aggregate RC one-way slabs. Six strengthened by NSM CFRP plates were presented to study the impact of several parameters on their structural behavior. The experimental results of four selected slabs under monotonic load, plus one slab under repeated load, were validated numerically. Then the numerical analysis was extended to different parameters investigation, such as the impact of added CFRP length on ultimate load capacity and load-deflection response and the impact of concrete compressive strength value on the structural performance of
... Show MoreThe intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is
... Show MoreRelease of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are
... Show MoreThis study presents, for the first time, an innovative Jet Plasma-assisted technique for the green synthesis of TiO₂@Ag core–shell nanoparticles using chard leaf extract as a natural reducing and stabilizing agent. The Jet Plasma provides a highly energetic environment that accelerates nucleation and core–shell formation at low temperatures without toxic precursors. The synthesized nanoparticles exhibited uniform and stable structures, as confirmed by comprehensive characterization techniques including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), ultraviolet–visible (UV–Vis) spectroscopy, transmission electron microscopy (TEM), and zeta potential analysis. XRD patterns confirmed the crystalline anatase
... Show MoreObjective(s): To assess the practices of early childhood’s mothers regarding toilet training and to find out the relationship between mothers’ practices and their socio-demographic characteristics and their children’s demographic characteristics.
Methodology: A descriptive study is conducted at primary health care centers in Al-Rusafa District in Baghdad City for the period of September 19th 2020 to March 16th 2021. Non probability “convenient” sample of (225) early childhood’s mothers is selected. A questionnaire format is designed and composed of two parts: the first part includes mothers’ socio-demographic characteristics and their children and the second part includes structured close-ended questions to assess the p
The δ-mixing of γ-transitions in 70As populated in the 32 70 70 33 Ge p n As (, ) γ reaction is calculated in the present work by using the a2-ratio methods. In one work we applied this method for two cases, the first one is for pure transition and the sacend one is for non pure transition, We take into account the experimental a2-coefficient for previous works and δ -values for one transition only.The results obtained are, in general, in a good agreement within associated errors, with those reported previously , the discrepancies that occur are due to inaccuracies existing in the experimental data of the previous works.
This research includes the synthesis of some new N-Aroyl-N \ -Aryl thiourea derivatives namely: N-benzoyl-N \ -(p-aminophenyl) thiourea (STU1), N-benzoyl-N \ -(thiazole) thiourea (STU2), N-acetyl-N ` -(dibenzyl) thiourea (STU3). The series substituted thiourea derivatives were prepared from reaction of acids with thionyl chloride then treating the resulted with potassium thiocyanate to affored the corresponding N-Aroyl isothiocyanates which direct reaction with primary and secondary aryl amines, The purity of the synthesized compounds were checked by measuring the melting point and Thin Layer Chromatography (TLC) and their structure, were identified by spectral methods [FTIR,1H-NMR and 13C-NMR].These compounds were investigated as a
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