Objectives: This study aims to evaluate the role of social media in promoting awareness of green university initiatives and assess the effectiveness of sustainability reports in engaging students at Baghdad University. In alignment with Sustainable Development Goal 12 (Responsible Consumption and Production),It seeks to provide recommendations for enhancing digital platforms for sustainability communication. Theoretical Framework: The study is grounded in the Green University Model, Social Media Engagement Theory, and the Sustainability Reporting Framework, which emphasize integrating sustainable practices in education, using digital platforms for community engagement, and leveraging sustainability reports for transparency and trust-building. Method: A quantitative research design was employed, involving a structured questionnaire administered to 100 elite students at Baghdad University. The study analyzed social media usage patterns, awareness of sustainability initiatives, and perceptions of sustainability reporting. Results and Discussion: The findings reveal a significant association between social media engagement and increased awareness of green initiatives. Key results indicate that 94% of participants follow the university's official social media outlets, and 70% reported behavior changes due to exposure to sustainability-related content. However, gaps in communication about sustainability-focused student groups were identified. The results align with existing literature while emphasizing the need for improved visibility and strategic communication. Research Implications: This study underscores the critical role of social media and sustainability reporting in fostering environmental awareness and behavior change among students. It provides a localized perspective that can guide other universities in Iraq and similar regions in adopting effective sustainability communication strategies. Originality/Value: By focusing on Baghdad University, this study addresses a research gap in understanding the unique challenges of sustainability communication in developing regions, offering actionable insights for enhancing academic and community engagement in green practices.
This paper presents a new Azo dye that was prepared from the reaction of the Benzene-1,2-diamine and 1-(2,4,6-Trihydroxy-phenyl)-ethanone, Azo dye was used to prepare a new series of complexes with general formula: [Co2(H4L) Cl2(H2O)4] and [M2(H4L)Cl4(H2O)2] (M= Cr+3, Fe+3,Rh+3 and Ru+3). The prepared materials were different measurements including to infrared, ultraviolet-visible, and mass spectrometry, as well as thermo gravimetric analysis, differential calorimetry, and elemental analysis. Conductivity, magnetic susceptibility, metal content, and chlorine content of the complexes were also assessed. The complexes prepared from the dye were used to determine their ability to inhibit free radicals by measuring their antioxidant capacity us
... Show MoreIn this research, the kinetic studies of four isoenzymes of Asprtate aminotransferase, which partially purified from the urine of chronic renal failure patients were carried out .The four isoenzymes were obeyed Michaelis-Menton's equation and the optimum concentration of their substrate (Aspartic acid) was (166.5x10-3) mole/liter,and their Km values were determined. Four isoenzymesI,II,III,IV have shown an optimum pH at 7.4.The four isoenzymes obeyed Arrhenius equation up to 37º C and their Ea and Q10 constants were determined .
The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
... Show MoreKE Sharquie, HR Al-Hamamy, AA Noaimi, KA Ali, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3
Accurate land use and land cover (LU/LC) classification is essential for various geospatial applications. This research applied a Spectral Angle Mapper (SAM) classifier on the Landsat 7 (ETM+ 2010) & 8 (OLI 2020) satellite scenes to identify the land cover materials of the Shatt al-Arab region which is located in the east of Basra province during ten years with an estimate of the spectral signature using ENVI 5.6 software of each cover with the proportion of its area to the area of the study region and produce maps of the classified region. The bands of these datasets were analyzed using the Optimum Index Factor (OIF) statistic. The highest OIF represents the best and most appropr
Release 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
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