5 results match your criteria: "Al-Imam Mohamed Ibn Saud Islamic University[Affiliation]"

Betalains from peels: UPLC-MS/MS metabolites profiling, computational investigation, and potential applicability as a raw meat colorant.

Heliyon

November 2024

Laboratory of Microbial and Enzymes Biotechnology and Biomolecules (LMEBB), Centre of Biotechnology of Sfax (CBS), University of Sfax-Tunisia, Road of Sidi Mansour Km 6, P. O. Box 1177, 3018, Sfax, Tunisia.

Given consumers', environmental and sustainability apprehensions, the meat industry investigated the natural colorant resources. As proof, betalain, peels (OSP) pigment, is premeditated in the meat industry. Here, OSP betalains were qualitatively profiled using UPLC-MS/MS, and 7 metabolites were identified: 6 betacyanins and a betaxanthin (arginine-betaxanthin).

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Exploring the Influence of Date Palm Cultivars on Soil Microbiota.

Microb Ecol

August 2024

Centre of Molecular and Environmental Biology (CBMA), Department of Biology, University of Minho, Campus of Gualtar, 4710-057, Braga, Portugal.

Plants thrive in diverse environments, where root-microbe interactions play a pivotal role. Date palm (Phoenix dactylifera L.), with its genetic diversity and resilience, is an ideal model for studying microbial adaptation to different genotypes and stresses.

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ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning.

PeerJ Comput Sci

October 2023

Department of Computer Science, College of Computer and Information Sciences, Al-Imam Mohamed Ibn Saud Islamic University, Riyadh, Saudi Arabia.

COVID-19 has become a global pandemic that has affected not only the health sector but also economic, social, and psychological well-being. Individuals are using social media platforms to communicate their feelings and sentiments about the pandemic. One of the most debated topics in that regard is the vaccine.

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Effect of visual imagery in COVID-19 social media posts on users' perception.

PeerJ Comput Sci

November 2022

Department of Computer Science, College of Computer and Information Sciences, Al-Imam Mohamed Ibn Saud Islamic University, Riyadh, Saudi Arabia.

People receive a wide variety of news from social media. They especially look for information on social media in times of crisis with the desire to assess the risk they face. This risk assessment, and other aspects of user reactions, may be affected by characteristics of the social media post relaying certain information.

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Brain-computer interface (BCI) technology uses electrophysiological (EEG) signals to detect user intent. Research on BCI has seen rapid advancement, with researchers proposing and implementing several signal processing and machine learning approaches for use in different contexts. BCI technology is also used in neuromarketing to study the brain's responses to marketing stimuli.

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