Abstract— Arabic language is characterized by its rich morphological structure, presenting unique challenges in Nat- ural Language Processing (NLP). The categorization of Arabic plurals is the subject of this study, which uses a trans- former-based model—more precisely, the pre-trained Arabic BERT architecture—and has never been studied previously. Given the complexities of Arabic language, particularly in pluralization which includes sound masculine, sound feminine, and irregular (broken) plurals, the research aims to enhance NLP capabilities in this area. By utilizing a dataset of 7,400 instances classified into four distinct categories, the study demonstrates the effectiveness of transfer learning in achieving high classification accuracy, with results indicating an accuracy of 97% across both validation and testing sets. Addition- ally, the model achieves high precision, recall, and F1-score metrics. A confusion matrix provides insights into classifica- tion performance, highlighting areas of misclassification. The findings underscore the potential of transformer models in overcoming the linguistic challenges posed by Arabic plural forms.

Fishes are considered as good indicators of heavy metals pollution in aquatic ecosystem in addition to being a good source of protein. Thus the level of Mercury (Hg) in fish which become a health hazard, was examined. The aim of the study was to determine the concentrations of Hg in the studied tuna fish samples. Moreover, evaluation of associated health risks from fish consumption were conducted of which, the intake rates of Hg was gauged based on Hg concentrations in fish muscles and the rate of daily fish consumption by Libyan population. A total of Forty-five specimens (20 canned tuna samples, local and imported samples, five frozen tuna samples and 20 fresh tuna samples) were sampled from different markets, large commercial centers, and food distribution points in the Tripoli area. A quantity of 0.5 grams of muscle completely homogenized mixture of each canned, fresh, and frozen tuna were digested by a mixture of 5 ml of nitric acid and 5 ml of sulfuric acid. A cold vapor atomic absorption spectrometer was utilized for the tuna fish analysis. The results showed that the concentrations of Hg were at the limits set by WHO and FAO, except for three frozen tuna samples were higher than the safety limits for human consumption, (2.33, 0.64, and 1.45 mg/kg wet. weight), and one fresh tuna sample (0.51 mg/kg wet. weight). The results revealed that, the average concentration of Hg for canned, frozen, and fresh tuna samples were calculated as 0.12, 1.02, and 0.19 mg/kg wet weight, respectively. However, the target hazard quotient (THQ) for Hg was less than 1 in the analyzed canned, frozen, and fresh tuna samples indicating no potential health risks to the population in studied area. However, the risk of health effects is increased due to the presence of Hg in seafood. Therefore, groups most at risk, including young children, the elderly, and pregnant women, limit their consumption of certain types of seafood, especially tuna. further comprehensive monitoring programs should be conducted.

For a composite number 𝒏, we explore a topological space on the ring of integers modulo 𝒏, we use basis sets formed by solutions to quadratic residue equations, where elements are units modulo 𝒏. This definition allows us to investigate the algebraic relationships among solutions, focusing on properties like clopen sets, closure, and interior operations. Additionally, we examine the continuity of mappings between the group of units in ℤ/𝒏ℤ and quadratic residues, alongside the quotient topology induced on this group of units. A comparison of the separation properties of these topological spaces is also presented

Abstract—Arabic Named Entity Recognition (NER) serves as a crucial facet within Natural Language Processing, given the intricacies of the Arabic language. This survey consolidates the current landscape of Arabic NER, covering methodologies, challenges, and advance- ments. The review encompasses an in-depth analysis of diverse approaches, from rule-based systems to modern deep learning techniques, highlighting their effectiveness and limitations. It also addresses the specific challenges inherent to Arabic NER, such as dialectal variations and limited annotated data, while exploring recent advancements and their applications in sentiment analysis, information retrieval, and other domains. This survey aims to provide a comprehensive overview, catering to researchers, practitioners, and enthusiasts in the field of Arabic NER and NLP.

ABSTRACT: This paper applies the Abaoub – Shkheam Decomposition Method (QDM) to obtaining solutions of linear fractional diffusion equations. The fractional derivative is described in the Caputo sense. Some illustrative examples are given, revealing the effectiveness and convenience of the method. 

This research documents the initial finding of Chloris pycnothrix Trin., frequently referred to as spiderweb chloris, in Libya, particularly from the Ariggiba region close to Sabha city. This grass, originating from tropical and subtropical regions, is versatile and may become invasive. It was recognized via morphological examination during field surveys in 2023–2024, with samples stored in a herbarium. The species flourishes in alluvial plains as well as in disturbed habitats like road shoulders. It can be mistaken for Chloris virgata, although they differ in some important morphological aspects. It was previously believed that only one species of Chloris existed in Libya. This study provides a revision and an identification key for them in the context of Libyan flora. The tolerant nature of C. pycnothrix to drought, combined with its ability to colonize poorly maintained land, makes its potential introduction—most likely through anthropogenic means—alarming ecologically and emphasizes the need for management strategies to contain its spread and monitor its impact. 

Abstract: In this paper, a nonlinear fractional diffusion and wave equations are solved using the Abaoub-Shkheam Decomposition Method (QDM). The Caputo sense is used to characterise the fractional derivative. An example is provided to demonstrate the method's efficiency and practicality.