Polyacrylonitrile nanofiber (PANFS), a well-known polymers, has been extensively employed in the manufacturing of carbon nanofibers (CNFS), which have recently gained substantial attention due to their excellent features, such as spinnability, environmental friendliness, and commercial feasibility. Because of their high carbon yield and versatility in tailoring the final CNFS structure, In addition to the simple formation of ladder structures through nitrile polymerization to yield stable products, CNFS and PAN have been the focus of extensive research as potential production precursors. For instance, the development of biomedical and high-performance composites has now become achievable. PAN homopolymer or PAN-based precursor copolymer can be employed to make CNFS. Water gets polluted because it throws industrial waste bodies of water, especially those containing dyes, heavy metals, and inorganic and organic wastes. Adsorbents, which are cheap and readily available, can be used to address the issue of water deterioration. According to this review, numerous PAN variations are being employed in scientific and technological settings. Nanocomposite fibers need extensive research efforts to advance technology and bring them to commercialization
Background: Asthma is one of the most common chronic respiratory diseases in the world, standing for the most frequent cause for hospitalization and emergency cases. Respiratory viruses are the most triggering cause. Aim: To assess the role of viral infections, especially COVID-19, in the pathogenesis of asthma initiation and exacerbations. Method: Electronic search was done for the manuscripts focusing on asthma as a risk factor for complications after COVID-19 infection. The outcomes were titles, materials, methods and classified studies related or not related to the review study. Three hundred publications were identified and only ten studies were selected for analysis. Seven studies were review, one retrospective, one longitudin
... Show More
(4)
The use of sugarcane molasses (SCM) as a sustainable stabilizing agent for geomaterials, particularly granular subbase soils, has recently attracted growing attention as an alternative to traditional stabilization methods employing cement, lime, or bitumen, which are often associated with high costs and environmental concerns. This study presents a mechanistic–experimental evaluation of SCM for stabilizing granular subbase materials at dosages of 2.5%, 5%, 7.5%, and 10% by weight of dry granular material. A comprehensive testing program was conducted, including compaction characteristics, California Bearing Ratio (CBR), resilient modulus (Mr), permanent deformation under repeated loading, optical microscopy, and FTIR spectroscopy.
... Show More
(2)
(1)
In this paper, three approximate methods namely the Bernoulli, the Bernstein, and the shifted Legendre polynomials operational matrices are presented to solve two important nonlinear ordinary differential equations that appeared in engineering and applied science. The Riccati and the Darcy-Brinkman-Forchheimer moment equations are solved and the approximate solutions are obtained. The methods are summarized by converting the nonlinear differential equations into a nonlinear system of algebraic equations that is solved using Mathematica®12. The efficiency of these methods was investigated by calculating the root mean square error (RMS) and the maximum error remainder (𝑀𝐸𝑅n) and it was found that the accuracy increases with increasi
... Show More
(2)
(1)
(30)
(23)
Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
... Show More
(40)
(41)
In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an
... Show More
(15)
(8)
(1)
(7)
(2)
Social media has become an essential educational tool nowadays. Most existing research on digital learning in EFL contexts has primarily focused on traditional classroom-based instruction and less attention has been paid to social media platforms. The present study aims to fill the gap by using social semiotics to analyze four Instagram posts: two from BBC Learning English (@bbclearningenglish) and the other two from Learn English with Emma (@englishwithemma). Instagram posts are classified as multimodal texts with participatory and representational elements. The study adopts Kress and van Leeuwen’s (2005) Social Semiotic Multimodal Framework to analyze four purposely selected posters by answering the following research questions
... Show More