Diabetic cardiac autonomic neuropathy (DCAN) is a significant condition that affects cardiovascular health worldwide and is associated with increased morbidity and mortality rates. Therefore, early detection and management of DCAN are crucial for reducing the risk of cardiovascular disease among individuals with T2DM. Identifying this disorder can enhance patient outcomes and quality of life by minimizing the chances of serious complications. This cross-sectional study aims to identify diabetic individuals with DCAN and to investigate its relationship with various risk factors, including hyperglycemia, the duration of diabetes, the presence of peripheral somatic neuropathy, and diabetic microvascular complications. The study included 261 patients with T2DM, comprising 61.5% females and 38.5% males. Participants underwent cardiovascular testing and clinical evaluations to identify cases of cardiac autonomic neuropathy. Out of the 261 randomly selected patients, 82 were diagnosed with DCAN, resulting in a prevalence rate of 31.4%. The average age for female patients was 57.5 ± 0.7 years, while for male patients, it was 56.3 ± 1.2 years from the total recruited patients. In addition, there is a strong association between DCAN and clinical and biochemical parameters such as lipid profile, duration of diabetes, poor diabetic control, and presence of microalbuminuria in patients with DCAN and above 60 years old, compared to younger patients. The study highlighted a strong association between DCAN and factors such as poor glycemic control, prolonged diabetes duration, and the presence of chronic microvascular complications, including neuropathy, retinopathy, and nephropathy. These findings emphasize the importance of raising awareness and proactively assessing Libyan patients who are at risk for cardiovascular autonomic neuropathy. This is crucial to reduce the likelihood of recurrent acute cardiac complications, especially in patients undergoing emergency surgery without a prior diagnosis. It is vital to recognize this risk.

Keywords. Type 2 Diabetes Mellitus, Pulse Rate, Metabolic Syndrome, Blood Pressure.

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.

Abstract— This survey explores different machine translation methods utilized in various systems and platforms for commercial and research purposes. These methods play a vital role in enabling global communication, enhancing accessibility, supporting business and trade, fostering intercultural understanding, facilitating travel and tourism, aiding education, delivering fast and efficient translations, contributing to humanitarian aid efforts, promoting research and collaboration, and preserving language and culture. The survey aims to equip software developers and researchers interested in machine translation with valuable insights into these methods. Its objective is to help them improve translation quality with great accuracy by providing them with the necessary knowledge and understanding of these approaches. The papers utilized in this survey were obtained from Open Access Journals and online databases. All these methods are essential and can differ based on the specific context, available resources, and the quality of the translation required. To achieve optimal translation results, researchers and practitioners commonly employ a combination of various methods and techniques. 

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: The exact solution of a nonlinear fractional Volterra-Fredholm integro-differential equation is found in this paper through the successful application of the Abaoub Shkheam decomposition method. These techniques have a wider range of applications due to their dependability and decreased computational effort. 

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. 

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.

Abstract: The Abaoub-Shkheam Decomposition Method (QDM) is employed in this paper to solve nonlinear initial value problems of second order. Adomian polynomial is used to decompose nonlinear functions that exist in a given equation. We are using this method (QDM) to find the exact solution of different types of non-linear ordinary differential equations, which is based on the Abaoub Shkheam transform method (QTM) and the Adomian Decomposition Method (ADM). An example is provided to demonstrate the efficacy of this approach. 

Professor Salem Aboglila                                                           

Geochemistry & Environmental Chemistry science Faculty – Azzaytuna University-Libya

Mobile : 00218913700361

            :00218923394183

Email: salem.aboglila@gmail.com 

Address: Salem Abdul Ghni Aboglila / TIP 52945, Aramex House Old Bath Road Colnbrook, Slough,Berkshire SL3 0NS 

Nov 2010 PhD degree Thesis title: Organic and Isotopic Geochemistry of Source-rocks and Crude Oils from the East Sirte Basin (Libya). Curtin University of technology (palaeoenvironment study)

Coronary artery disease (CAD) is the leading cause of death worldwide. the study aims to evaluate the association between plasma lipoprotein-associated phospholipase A2 (Lp-PLA2) and Libyan individuals' clinical and biochemical risk factors for CAD. This cross-sectional study assessed plasma concentration of Lp-PLA2 between patients with CAD and those without CAD in both genders based on clinical history, exercise ECG, two-dimensional echocardiography, and coronary angiography. Several biochemical parameters were estimated. Plasma levels of Lp-PLA2 were measured. 181 individuals were recruited for this study, including 125 with CAD and 56 without CAD. Plasma Lp-PLA2 concentration was significantly higher in patients with CAD versus individuals without coronary artery disease. In addition, the plasma concentration of Lp-PLA2 was higher in patients >60 years of age compared with patients <60 years old. To conclude Plasma level of Lp-PLA2 concentration was independently correlated with CAD, an inflammatory marker such as high sensitivity C-reactive protein among Libyan patients.