This research investigated the challenges medical university students encounter in learning

technical vocabulary. A quantitative research approach was adopted. 61 first-year medical

students at the University of Gharyan participated in the study. A structured questionnaire was

used to gather the data. The findings revealed that medical university students encounter

several challenges in medical vocabulary learning, including pronunciation, spelling, meaning and use. The results also indicated that medical university students struggle to recall some

medical terms, which could be attributed to cognitive overload. The researchers suggest

revaluating the current English medical programs at the Faculties of Medicine in Libya.

Teaching vocabulary in context, highlighting the grammatical categories of words, drawing

distinctions between synonyms through examples, and training students on using medical

words through interactive activities could enhance the current English medical programs.

SUMMARY 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 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. 

ABSTRACT

This study aimed to explore EFL teachers’ perceptions of the 21st-century PD program in six primary schools in Al Jabal Al Gharbi district. 31 teachers participated in the study. The mixed-research approach was used to conduct the research. A structured questionnaire and a semi-structured interview were used to gather the data. The results revealed that participants acquired several teaching skills, such as new techniques for teaching vocabulary, speaking, and listening language skills, from the 21st-century PD program. Furthermore, the participants reported positive changes in their students’ outcomes, including improved speaking, listening and vocabulary. The findings also revealed some complications in implementing the PD program, including a lack of resources and administrative support at some schools.

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.

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.