In recent years, English language learners are becoming highly dependent on the 

use of their smart phones to find out meanings of the vocabulary they usually do 

not know. A study by Soy (2022) highlighted that English language teachers need 

to introduce the use of smartphones as a learning tool to their students and take 

serious actions by not allowing them to use them during classes or making good 

classroom management and strict regulation concerning smartphone use in the 

classroom. The researcher in this paper attempts to shed lights on research 

conducted in this field by exploring advantages and disadvantages of the use of 

smartphones by (EFL) English language learners. This paper aims to identify the 

effectiveness of smartphones in enhancing language acquisition among learners 

by synthesizing data from various studies. The data of this study included 

analyzing 47 articles published between (2014) and (2023). The topics of the 

articles predominately were about smartphones and English language learning. 

This simple paper offers valuable insights for educators and stockholders seeking 

to optimize smartphone use in language education.

Abstract The integration of Artificial Intelligence (AI) in education is progressively transforming teaching, learning, and administrative practices globally, with significant potential for application in Libya. the purpose of this research is to discuss and evaluate the benefits and risks of AI in the education system of Libya. To achieve this, a descriptive research approach was employed, using a questionnaire distributed to a selected group of educational professionals in Libya. The sample consisted of 1,000 participants, and the survey was conducted via the WhatsApp application. The results highlight that personalized learning received the highest mean score of 4.19, indicating strong agreement on its effectiveness. Automation of administrative tasks (mean 3.80) and data-driven decision-making (mean 3.98) also showed favorable perceptions, with low variances around 0.24 0.25, reflecting consistent responses. Improved student engagement had a mean of 3.91 and a standard deviation of 0.49, similar to others, suggesting overall positive and uniform attitudes. Additionally, most responses clustered around neutral to moderate agreement, with modes of 3 or 4, showing balanced or mildly supportive opinions. Variance values ranging from 1.39 to 1.48 suggest a moderate spread, indicating some disagreement among participants. Standard deviations around 1.18 to 1.21 confirm a consistent yet moderate level of variability, without extreme polarization The obtained results show strong agreement on the benefits of educational innovations, especially personalized learning, which had the highest mean, and all aspects scored highly with low variability, indicating consistent positive perceptions. At the same time, the conclusions reveal moderate concern among respondents about the cost and inequality issues related to AI in education, with variance and standard deviation values reflecting a consistent spread of opinions. This research contributes to the academic discourse on the impactful integration of AI in academic institutions and establishes positive perceptions for continual enhancement. Overall, funding infrastructure emerges as the most pressing challenge, with general agreement across participants. Keywords. Artificial Intelligence, Education, Personalized Learning, Libya. 

This paper proposes a novel robust blind color image watermarking technique that combines entropy analysis, lifting wavelet transform (LWT), QR factorization, and discrete cosine transform (DCT) for copyright protection. The RGB components of the color image are first separated, and the R component is then subjected to the 2-level LWT. Following DCT is applied to the 2-level LWT's high-frequency sub-band, the DCT coefficients are separated into 4x4 non-overlapping blocks. Each chosen block is then subjected to QR factorization, and the watermark is embedded in the first row and first column element of the upper triangular matrix. Numerous simulated tests show that the presented scheme is highly imperceptible and robust to attacks. The presented watermarking scheme performs better than the others in terms of invisibility, according to comparisons with comparable schemes.

ABSTRACT

Argemone ochroleuca Sweet, Brit. Fl. Gard. Ser.1 3(2): pl. 242 (1828) of the family Papaveraceae is reported here for the first time from Libya. This species is native to Mexico. Flowering specimens of A. ochroleuca were collected from the region Ariggiba (26°35’11.8”N 13°29’24.8”E), 110 km southwest of the city of Sabha, which lies about 700 km south of Tripoli. It is presented with updated nomenclature, taxonomic description, geographical distribution, key to genera, location in Libya, and colour photographs taken in the field. The voucher specimens are deposited in the Herbarium of Botany Department (ULT), University of Tripoli, Libya.

Urinary tract infections (UTIs) are considered the most widespread bacterial infections and among the most common nosocomial infections, second only to lower respiratory tract infections. The risk of developing a UTI increases with age, making UTIs among the most commonly diagnosed infections in elderly people, representing a significant public health problem. This study aimed to isolate and detect the microbial responsible for urinary tract infections in elderly individuals and determine their resistance patterns and sensitivity to antibiotics among Libyan patients in Tripoli city. The study was conducted simultaneously in Alsharik, Eltafoq, and Ibn Al Nafis laboratories in Tripoli, Libya, during July and August 2024. One hundred and one urine samples were collected from elderly participants suffering from UTI symptoms (38 males and 63 females), with ages ranging from 60 to 97 years. Isolation, biochemical identification, and antibiotic susceptibility analyses were performed. Thirteen antibiotics were testedin this study. Among the 101 isolated samples from elderly patients with suspected UTI, females had a higher prevalence of bacterial infections (62.4%) compared to males (37.6%). The highest number of infections was in the 60–69 years age group (45.4%). Gram-negative organisms accounted for 91.1% of isolates compared to Gram-positive organisms. Escherichia coli was the most common organism isolated (43.6%), followed by Klebsiella pneumoniae (29.7%). Most isolates were resistant to Ampicillin (31.7%) and Amoxicillin (23.8%), followed by Tetracycline (10.9%). The Gram-positive organisms Streptococcus pneumoniae, Enterobacter spp., and Staphylococcus aureus were most susceptible to Amoxicillin, Amikacin, and Meropenem, with sensitivity rates of 75%, 66.7%, and50%, respectively. E. coli was more susceptible to Imipenem (25%), Amikacin (22.7%), and Nitrofurantoin (13.6%), whereas Amoxicillin and Sulfamethoxazole/Trimethoprim showed lower efficacy. Gram-negative bacteria were the main cause of UTIs in the study population, mainly belonging to the E. coli and Klebsiella families. Age and gender were significant factors in determining UTI etiology, and considering these factors can improve the accuracy in identifying causative uropathogens and guide empirical treatment.Keywords:UTI, Antibiotic Resistance, Sensitivity Antibiotics, Uropathogenic E.Coli

مؤخرًا برزت عدة تساؤلات حول طبيعة علاقة الذكاء الاصطناعي بالذكاء البشري، فالهدف من هذه الدراسة هو مناقشة فرضية أن العلاقة بين الذكاءين يجب أن تُبنى على التكامل لا على التنافس. واعتمدت الدراسة على المنهج الوصفي التحليلي من خلال مراجعة الأدبيات الحديثة التي تناولت الإمكانات التكاملية بينهما.. كما واوصت الدراسة بتبني اطار تعاوني تشاركي (الذكاء التشاركي) والذي يعزز التفاعل الايجابي بين الانسان والآلة..