MSA Repository "MSAR"

MSAR University's Digital Repository is a documentation and digitization of all university outcomes that are of effective value in the scientific and academic community and reflects the university's image, work, and effective contribution to society Through MSAR Digital Repository, the university managed to collect, store, archive and publish digital content - including documents, audio files, images and data sets - all in a safe place. MSAR is one of the strongest University Digital Repositories in Egypt and documented in the DSPACE community with its latest versions.

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A Guide to Basic RNA Sequencing Data Processing and Transcriptomic Analysis
(Bio-protocol LLC, 2025-05-05) Rowayna Shouib; Gary Eitzen; Rineke Steenbergen
RNA sequencing (RNA-Seq) has transformed transcriptomic research, enabling researchers to perform largescale inspection of mRNA levels in living cells. With the growing applicability of this technique to many scientific investigations, the analysis of next-generation sequencing (NGS) data becomes an important yet challenging task, especially for researchers without a bioinformatics background. This protocol offers a beginner-friendly step-by-step guide to analyze NGS data (starting from raw .fastq files), providing the required codes with an explanation of the different steps and software used. We outline a computational workflow that includes quality control, trimming of reads, read alignment to the genome, and gene quantification, ultimately enabling researchers to identify differentially expressed genes and gain insights on mRNA levels. Multiple approaches to visualize this data using statistical and graphical tools in R are also described, allowing the generation of heatmaps and volcano plots to represent genes and gene sets of interest.
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Second glance: exploring consumer shifts to thrift shopping and perception of second-hand fashion
(Springer open, 2025-05-03) Nancy Ahmed Mobarak; Nada Ali Amin; Ahmed Abdel‑Mohssen; Ahmed Sharif; Yasser Tawfk Halim; Karen Brickman
Purpose The increasing consumer interest in second-hand fashion is reshaping the retail landscape, yet concerns about perceived risks and value continue to infuence purchasing behaviors. While existing research highlights sustainability and afordability as key drivers of thrift shopping, the impact of perceived risks (functional and social) on customer switching behavior remains underexplored. This study examines how consumer perceptions of secondhand clothing infuence their decision to switch from new to used fashion, integrating theories of perceived risk and customer switching behavior. By addressing this gap, the study contributes to a deeper understanding of the barriers and motivations behind second-hand clothing adoption. Design/methodology/approach This study employs a mixed-method approach to comprehensively analyze consumer switching behavior toward second-hand clothing. The qualitative phase includes in-depth interviews with an industry expert and 20 hand clothing consumers, providing nuanced insights into motivations and perceived barriers. The quantitative phase consists of an online survey with 290 respondents, statistically examining the relationships between perceived risks and switching behavior using correlation analysis and reliability testing. By integrating both qualitative and quantitative insights, this study ensures a holistic understanding of the factors infuencing second-hand clothing adoption. Findings Analysis of the data using SPSS revealed that customers’ perceptions signifcantly afect their switching behavior concerning second-hand clothes. Originality/value This research contributes to the understanding of the dynamics between customer perception and market behavior in the context of second-hand clothing, highlighting the role of perceived risk in consumer decision-making processes.
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Real-World Vehicle Estimation and Control of Indirect Emissions Control and Performance Evaluation of Electric Vehicles with In-Wheel Motors
(SAE International, 2025-03-18) Mohamed S. Shiba; Shawki A. Abouel-Seoud; W. Aboelsoud; Ahmed S. Abdallah
The growing number of automobiles on the road has raised awareness about environmental sustainability and transportation alternatives, sparking ideas about future transportation. Few short-term alternatives meet consumer needs and enable mass production. Because they do not accurately reflect real-world driving. Current models are unable to estimate vehicle emissions. However, the purpose of this research is to present an application of an adaptive neuro-fuzzy inference system for managing the various factors contributing to vehicle gasoline engine exhaust emissions. It examines how well the three known standardized driving cycles (DSCs). Accurately reflect real-world driving and evaluate the impact of real-world driving on vehicle emissions. Indirect emissions are inversely proportional to the vehicle's fuel consumption. The methodology used is Eco-score methodology to calculate indirect emissions of light vehicles. Expected emission charge estimates for different using styles. Emission rates range substantially between battery classes. The vehicle's gasoline efficiency is four times better than a similar automobile, but neither mass nor charge multiplied appreciably. The range of this car is not restrained by the battery length, which increases driver comfort, while automobile meets customer expectations in addition to environmental worries and advantages. Despite the fact that they continue to be affordable, they offer a possibility for mass manufacturing reducing overall environmental effects. In keeping with the consequences, the adaptive neuro-fuzzy inference system works nicely to simulate and regulate vehicle engine exhaust emissions. However, the final objective of a regulatory-oriented studies software that focuses on air pollution from mobile sources is to identify and quantify any outcomes that the emissions may have on human fitness. However, before we invest highbrow and economic sources, we need to first recognize the restrictions of modern information and methodologies that preclude accurate estimates of risk to human health. Destiny research packages should be justified by way of their promise to triumph over these boundaries. The goal of this extent, then, is to identify troubles and pick out a studies schedule with a purpose to be only in advancing our potential to quantify the fitness dangers related to air pollution.
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Quantifying Visual Navigation in Campus Open Spaces Using a Computer Vision Model
(John Wiley and Sons Inc, 2025-04-24) Nabil Mohareb; Abdelaziz Ashraf
This study presents a framework specifically designed to measure and quantify visual experiences within academic campus environments. The framework addresses the need for quantitative methods to analyze spatial experiences, focusing on key elements of the built environment, such as visible sky, greenery, and spatial enclosure. While the framework emphasizes visual components, it does not aim to analyze broader sensory or emotional experiences. Instead, it establishes a foundation for future research to explore these dimensions comprehensively. The methodology utilizes mobile phones equipped with digital cameras and GPS sensors to capture first-person visual data while participants freely navigate through campus open spaces. Computer vision techniques, including instance segmentation and convolutional neural networks, are employed to categorize architectural and natural elements within each video frame. This process quantifies the proportional composition of visual elements such as greenery, open sky, walkways, buildings, and other structures that participants encounter. The framework is implemented as a Python model that is capable of generating quantitative outcomes. Additionally, the analysis is enhanced by integrating geographic information systems (GISs) for spatial analysis, allowing us to identify navigation and visual engagement patterns. This comprehensive methodology not only quantifies the visual attributes of spaces but also interprets their impact on the behavior and experiences of campus users. This framework offers insights into how navigation choices, visual experiences, and the types of scenes encountered on campus can be understood and analyzed. The results aim to guide urban designers in better understanding university students’ open space needs by exploring the connections between natural movement patterns and visual preferences. This research complements other qualitative approaches, providing a more comprehensive perspective on campus space utilization.
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Metabolomic analysis reveals key changes in amino acid metabolism in colorectal cancer patients
(Springer, 2025-05-02) Asmaa Ramzy; Taghreed Khaled Abdelmoneim; Menna Arafat; Maha Mokhtar; Ashraf Bakkar; Amany Mokhtar; Wagida Anwar; Sameh Magdeldin; Shymaa Enany
The number of colorectal cancer (CRC) patients is steadily growing worldwide, particularly in developing nations. Nonetheless, recent advances in early detection studies and therapy alternatives have reduced CRC mortality in afuent countries, despite rising incidence. Gut microbiota and their metabolites may contribute to tumor growth and reduced therapeutic efcacy. This preliminary study sought to uncover metabolic fngerprints in colorectal cancer patients. It also emphasizes the correlation between the gut microbiome, microbial metabolism, and altered metabolites in CRC. In this study, stool samples from 20 CRC patients and matched healthy controls were enrolled. Untargeted metabolomics approach based on an ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-MS/MS) were applied. Statistical approaches, pathway enrichment analysis, and network analysis were employed to unleash CRC perturbed metabolic pathways and putative biomarkers. The study identifed a distinct manually curated metabolite profle that is substantially linked to CRC. The steroidogenesis, aspartate, tryptophan (Trp), and urea cycle were the most signifcant pathways that concurrently contributed to CRC.Prominently, among other pathways, Trp metabolism was identifed as a critical pathway, indicating a possible connection between the development of CRC and gut microbiota. In a nutshell the notable resulted metabolites reveal auspicious biomarkers for the initial diagnosis as well as surveilling of CRC progression. This preliminary study highlights the potential involvement that gut bacteria may contribute in CRC patients. Further investigation into the composition of the gut microbiome associated with this metabolic profle may lead to the identifcation of novel biomarkers for early detection and possible targets for treatment.