Recently a large number of extensive studies have amassed that describe the removal of dyes from water and wastewater using natural adsorbents and modified materials. Methyl orange dye is found in wastewater streams from various industries that include textiles, plastics, printing and paper among other sources. This article reviews methyl orange adsorption onto natural and modified materials. Despite many techniques available, adsorption stands out for efficient water and wastewater treatment for its ease of operation, flexibility and large-scale removal of colorants. It also has a significant potential for regeneration recovery and recycling of adsorbents in comparison to other water treatment methods. The adsorbents described herein were classified into five categories based on their chemical composition: bio-sorbents, activated carbon, biochar, clays and minerals, and composites. In this review article, we want to demonstrate the capacity of natural and modified materials for dye adsorption which can yield significant improvements to the adsorption capacity of dyes such as methyl orange. In addition, the effect of critical variables including contact time, initial methyl orange concentration, dosage of adsorbent, pH, temperature and mechanism on the adsorption efficiency will be covered as part of this literature review.
The Wheat husk is one of the common wastes abundantly available in the Middle East countries especially in Iraq. The present study aimed to evaluate the Wheat husk as low cost material, eco-friendly adsorbents for the removal of the carcinogenic dye (Congo red dye) from wastewater by investigate the effect of, at different conditions such as, pH(3-10), amount of adsorbents (1-2.3gm/L),and particle size (125-1000) μm, initial Congo red dye concentration(10, 25 , 50 and 75mg/l) by batch experiments. The results showed that the removal percentage of dye increased with increasing adsorbent dosage, and decreasing particle size. The maximum removal and uptake reached (91%) , 21.5mg/g, respectively for 25 initial concent
... Show MoreAI in teaching English is reshaping language learning. While interest in AI-supported education is growing worldwide, research in this area is still emerging in Iraq. This review synthesizes empirical AI-based intervention studies to enhance English language learning in Iraqi higher education, and the perceptions of stakeholders regarding AI tools in language instruction. The reviewed intervention studies, comprising studies employed different AI platforms to support grammar instruction, speaking fluency, writing feedback, and pragmatic competence. These interventions yielded improvements in learners’ performance, motivation, and communicative confidence. In parallel, perception-focused studies revealed positive attitudes toward A
... Show MoreTranslating news between Arabic and English is more complex than it may initially appear. The process is far more than the process of finding the same words, as it usually touches upon the structural differences, cultural allusions, and in most situations, the ideological pressure. This critical literature review is based on a narrative synthesis of 18 peer-reviewed studies published from 2023 to 2026 and explores the interaction of these factors in real journalistic practice. An even closer examination of the literature indicates that there are three common points of challenge. Firstly, structural and lexical differences between Arabic and English can be observed that have to be constantly adjusted to. Second, cultural and religious allusi
... Show MoreThe unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
Reducing costs and protecting the environment surrounding economic unity has become the concern of many economic units and shifting their ideas towards preserving resources and protecting the environment by adopting strategies and techniques that take into account when applied reducing production costs and protecting the environment, including these strategies and techniques, the technical costs of the product life cycle and the strategy of cleaner production, as the application of the two concepts in local economic units helps to try to keep up with the countries that work to keep up with the success of their economic units by following the concepts that have been successful in Developed countries by maintaining the sustainabilit
... Show MorePrediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered
... Show MoreThe aim of this paper was to investigate the removal efficiencies of Zn+2 ions from wastewater by adsorption (using tobacco leaves) and forward osmosis (using cellulose triacetate (CTA) membrane). Various experimental parameters were investigated in adsorption experiment such as: effect of pH (3 - 7), contact time (0 - 220) min, solute concentration (10 - 100) mg/l, and adsorbent dose (0.2 - 5)g. Whereas for forward osmosis the operating parameters studied were: draw solution concentration (10 - 150) g/l, pH of feed solution (4 - 7), feed solution concentration (10 - 100) mg/l. The result showed that the removal efficiency by using adsorption was 70% and the removal efficiency by using forward osmosis was 96.2 %.
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