This research delves into the realm of asphalt technology, exploring the potential of nano-additives to enhance traditional asphalt binder properties. Focusing on Nano-Titanium Dioxide (NT), Nano-Aluminum Oxide (NA), and Nano-Silica Oxide (NS), this study investigates the effects of incorporating these nanomaterials at varying dosages, ranging from 0% to 8%, on the asphalt binder’s performance. This study employs a series of experimental tests, including consistency, storage stability, rotational viscosity, mass loss due to aging, and rheological properties, to assess the impact of nano-additives on asphalt binder characteristics. The findings indicate a substantial improvement in the consistency of the asphalt binder with the addition of nanomaterials, particularly NS, which shows a 41% reduction in penetration at an 8% content and a notable increase in the softening point. The storage stability tests reveal that NS-modified asphalt exhibits superior stability compared to NT and NA, with a significantly lower ΔT increase. Furthermore, the investigation into rotational viscosity suggests that NS, despite increasing the binder’s viscosity, does not exceed the AASHTO M320 threshold, ensuring the binder’s workability. Aging tests demonstrate that NT, at lower concentrations, acts as an effective anti-aging agent, whereas NA and NS tend to increase the mass loss, impacting thermal stability. This study concludes that while each nanomaterial uniquely influences the asphalt binder’s properties, NS stands out in terms of enhancing the high-temperature performance and storage stability. Optimal dosages of 6% for NT and NA and 4% for NS are recommended based on the Overall Desirability analysis. This research bridges the gap between traditional asphalt materials and modern requirements, highlighting the transformative impact of nano-additives in advancing asphalt pavement technology.
A resume is the first impression between you and a potential employer. Therefore, the importance of a resume can never be underestimated. Selecting the right candidates for a job within a company can be a daunting task for recruiters when they have to review hundreds of resumes. To reduce time and effort, we can use NLTK and Natural Language Processing (NLP) techniques to extract essential data from a resume. NLTK is a free, open source, community-driven project and the leading platform for building Python programs to work with human language data. To select the best resume according to the company’s requirements, an algorithm such as KNN is used. To be selected from hundreds of resumes, your resume must be one of the best. Theref
... Show MoreIn this work, the effects of solvent properties on the characteristics of absorption and fluorescence for two laser dyes was studied. Dyes used in this work include Coumarin 5400 and DCM, while the solvents include ethanol, methanol, acetone, propanol and chloroform. Coumarin 5400 dye shows sharp fluorescence peaks in the green band of visible region while the DCM dye shows relatively wide band within 590-630 nm. Therefore, the selection of any dye for random gain medium applications should be performed after determining the most appropriate solvent as the optimum fluorescence characteristics are obtained.
English is spoken by its native speakers in two different forms. Reduced form which marks the colloquial and rapid speech so that it is easily produced and a citation or unreduced form which is a characteristic of careful, emphasized and slow speech.
This paper investigates Iraqi EFL university students’ production of the two forms mentioned above. The sample chosen includes twenty fourth year students, of which ten are males and the other ten are females from the Department of English of the College of Languages of the University of Duhok in Kurdistan Region of Iraq in the academic year 2020-2021. The material tested is six connective words which represent the commonest ones in every-day co
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