ABSTRACT

This article presents another method to improve the performance

and efficiency of a gas-fired power plant in Al-Zawia, Libya. In

order to improve power plant efficiency and increase power, the

principle of a heat recovery steam generator (HRSG), which is

mainly based on the waste heat energy of exhaust gases generated

by a simple gas turbine unit, is a method that can be used for

improvement. The present system was simulated using Aspen

HYSYS software. For validation purposes, the simulation results

were compared with the actual operating data, net power and

thermal efficiency of the cycle under the same conditions. These

results show a high level of agreement between theoretical and

practical data. This agreement enables and provides good

implementation to use this software to simulate an entire combined

cycle. In addition, operating parameters that influence power plant

performance were examined. The results show that the combined

cycle improved the thermal efficiency and net power output by

49.8% and 50%, respectively, under the same operating conditions.

The results also showed that compressor pressure ratio and inlet air

temperature have significant effects on thermal efficiency and net

power produced in both simple and combined power plants

This paper presents the development of an advanced system designed to efficiently process Arabic queries in today’s data-driven landscape. By using the T5 sequence-to-sequence model developed by Google and fine-tuning it specifically for transforming textual and verbal input into SQL queries, the system becomes adept at accurately comprehending and interpreting Arabic queries.

The resulting system serves as a user-friendly tool that automates the generation of SQL queries. Users can input their queries in written or recorded Arabic utterances, eliminating the need for manual translation and query construction.

This involved fine-tuning T5 models on a SQL dataset, splitting the dataset, tokenizing it, and setting training parameters. The implementation phase included loading the fine-tuned model, which incorporated PICARD to generate valid queries effectively. This paper also explores the impact of Arabic translation on the performance and accuracy of the model.

The optimal testing on test set accuracy achieved was 63.11%, the real-world testing accuracy: T5-base without PICARD scored 56.96% and 51.36% on English and Arabic questions, respectively, while T5-large with PIARCD scored 77.74% and 70.34% on English and Arabic questions.

Abstract :

Antibody tests can identify people with a resolving or past severe acute respiratory syndrome coronavirus 2 infection and thereby help researchers and public health experts better understand the epidemiology of severe acute respiratory syndrome coronavirus 2. This study is a retrospective study that included 187 Libyan individuals, who attended Attshkhesy (the diagnostic) laboratory in Alkhoms City, Libya, between January 01, 2021, and August 28, 2021. The mean ages of males and females were 48.8 and 46.8, respectively. The study utilized the CLIA quantitative antibody test. To perform the CLIA quantitative antibody test, a high throughput assay apparatus known as the YHLO - iFlash 1800 Chemiluminescence Immunoassay Analyzer was utilized, along with assay reagents called iFlash-SARS-CoV-2 IgM/IgG (manufactured by YHLO Biotech, Shenzhen, China). In female subjects, the concentration of severe acute respiratory syndrome coronavirus 2 IgM was higher than that of IgG in all age groups. Interestingly, in male subjects, the results showed the opposite, where the concentration of severe acute respiratory syndrome coronavirus-2 IgG was much higher than that of IgM in all age groups. When male data were plotted against the female data, the concentration of severe acute respiratory syndrome coronavirus 2 IgM in females was much higher than that of IgM in males in all age groups. Merged IgM-male and IgM-female results showed that IgM concentrations were higher in females than males at all age groups, which means that the incidence of recent COVID-19 infection was higher in females than in males. On the other hand, the IgG antibody prevalence in females was always higher than in males except at age groups 41-50 years and 51-60 years, which can be used as an indicator of high acquired immunity among females due to possible reinfection of females with COVID-19 virus.

L'introduction de cet essai cherche à montrer l'importance croissante de la langue française en Libye, qui se retrouve au centre d'interactions culturelles et économiques dans le pays. L'influence passée et coloniale de la France a laissé une marque importante sur les relations entre les deux pays et sur le système éducatif libyen. Ainsi, savoir parler français devient un enjeu majeur pour les Libyens, que ce soit pour trouver des emplois ou pour mieux comprendre les cultures qui parlent français. Dans un monde de plus en plus interconnecté, le français n'est pas seulement un outil de communication, mais aussi une porte qui s'ouvre vers de nouvelles opportunités, académiques et sociales. L'image montre cette dynamique à travers une étude de la production académique qui soutient l'enseignement du français en Libye, mettant en lumière les défis actuels de cette compétence linguistique.

This cross-sectional study aims to examine the depressive symptoms and stress among older adults. A convenience sample (n = 547) of older adults aged 60+ years was recruited from various regions in Libya. The WHO-5 and PSS-10 were used to assess depression and stress levels. The level of depressive symptoms and stress were 68 % and 71.5 %, respectively, with males reported more depression and stress than females (p ˂ 0.05). A combination of stress and family status significantly associated with levels of depression among the participants. This study provides important insights into the psychological health status of older adults in Libya. The high levels of depression and stress, as well as the identified correlates, shed light on the factors influencing mental well-being in this vulnerable population. These findings can serve as a foundation for the development of targeted interventions aimed at promoting the mental health of older adults in Libya.

Sarcasm is often used to convey the opposite of what is actually said (positive words, negative meaning). It is a type of humor that relies on the listener or reader to understand the intended meaning of the words. Sarcasm can be difficult to detect in written text, especially on social media platforms where people often use abbreviated language and emojis to convey their messages. The sarcasm detection can be a crucial role in refining Automated Sentiment (SA). In order to enhance the effectiveness of data-driven approaches for customer service and product development. Furthermore, the existing research on sarcasm detection in Arabic is limited. Also, there is a noticeable absence of studies in particular, the sarcasm detection in Libyan Arabic dialects. This study utilizes a data-set of 5082 collected from Facebook platform, labeled by team annotators experienced in the Libyan dialects as (sarcastic or non-sarcastic), and extracting some lexical and syntactic features which used to training Support Vector Machine (SVM) model. The results show commendable performance with an accuracy of 79.15%, precision of 79.3%, recall of 79.7%, and an F1 score of 79.5%.