This study aimed to assess and compare the therapeutic effectiveness of fresh latex derived from

male and female

Ficus

carica

L

trees as a natural

treatment for common warts

.

Fresh latex was

collected from immature green fruits of male and female trees and applied topically to 62 warts in

28 patients, three times weekly. Clinical responses were documented over a four

-

week period.

Both types of latex

produced measurable therapeutic effects, characterized by progressive

shrinking, drying, and detachment of warts. Male latex demonstrated significantly faster action:

initial flaking occurred by day 3, with complete resolution observed in most lesions wit

hin 12

–

21

days. Female latex required longer treatment times, with full regression occurring between 15 and

30 days

.

The superior efficacy of male latex may reflect differences in biochemical composition,

including higher or more active concentrations of p

roteolytic enzymes (e.g., ficin), organic acids,

phenolics, triterpenoids, and antioxidant

-

related proteins such as chitinase and peroxidase. These

compounds may synergistically produce antiviral, keratolytic, and cytotoxic effects on

human

papillomavirus

(

HPV)

-

infected keratinocytes. No severe adverse reactions were reported, and only

mild discomfort occurred in sensitive areas

.

This study provides the first comparative evidence

supporting fig latex, particularly from male tree, as a simple, inexpensive,

and natural therapeutic

option for common warts

Abstract:

Computer-mediated communication (CMC) and social networking sites have transformed the conditions

under which written English is produced, circulated, and interpreted. This paper examines how these

environments influence English spelling and orthography, with particular attention to Netspeak and

Facebook-speak. It also considers whether non-standard digital forms should be treated primarily as

evidence of linguistic deterioration or as systematic resources adapted to the communicative demands

of online interaction. The study adopts a qualitative, literature-based analytical design. It synthesizes

historical accounts of English spelling with findings from previous studies of online language, including

research on Facebook writing, capitalization on Twitter, and the relationship between social networking

practices and students' academic writing. The analysis identifies recurrent digital orthographic features

such as abbreviations and acronyms, non-standard spellings, contractions, omitted or repeated

punctuation, unconventional capitalization, emoticons, hashtags, and reduplicated letters. Evidence

reviewed from earlier studies suggests that some of these features may transfer into students' academic

writing, particularly when genre boundaries are weak; however, the same features also perform

meaningful functions related to speed, brevity, prosody, stance, emphasis, and social identity. The

paper concludes that CMC does not simply damage English spelling. Rather, it creates a context in

which standard and non-standard orthographic practices coexist. Educational responses should

therefore emphasize register awareness and the ability to distinguish informal digital writing from formal

academic writing, rather than treating digital language as inherently deficient.

Keywords: Computer-Mediated Communication, social media, English Spelling, Orthography,

Netspeak, Facebook-speak, Digital Literacy.

This study proposes a new robust blind video watermarking technique for copyright protection that combines the Fourier transform, entropy analysis, Hessenberg decomposition, and lifting wavelet transform (LWT). The host video is divided into frames, the RGB channel of each frame is then isolated, and the 2-level LWT is applied to the R channel. The FFT coefficients are divided into 4x4 non-overlapping blocks after the FFT is applied to the high-frequency sub-band of the 2-level LWT. The watermark is then hidden in the first row and first column element of the upper Hessenberg matrix after each selected block has been subjected to Hessenberg decomposition. The proposed technique is extremely invisible and resilient to attacks, as demonstrated by numerous simulated experiments. Comparisons with similar scheme show that the proposed watermarking scheme outperforms the others in terms of invisibility and robustness

Abstract

This study explores the integration of Artificial Intelligence (AI) into English Language Teaching (ELT), with particular emphasis on its role in supporting teachers, enhancing language skills, personalizing instruction, and promoting learner autonomy. The research investigates teachers’ and learners’ perceptions of AI-assisted English language education and its effectiveness in developing speaking, listening, reading, writing, vocabulary, grammar, and pronunciation. Using a questionnaire-based research design, the study examines participants’ experiences with AI-supported learning and teaching. For illustration, a results section could report that 76.0% of participants found AI useful or very useful for English language practice, 68.0% reported that immediate AI-supported feedback helped them identify language errors, and 72.0% believed that personalized AI activities increased opportunities for independent practice. From the teaching perspective, 80.0% could report that AI was useful for preparing or adapting instructional materials, while 84.0% could agree that AI should be used as a supplementary educational tool rather than as a replacement for qualified English language teachers. The findings would suggest that AI has considerable potential to enhance English language education when integrated within a structured pedagogical framework. AI can support differentiated instruction, provide additional opportunities for language practice, facilitate immediate feedback, and assist teachers with lesson preparation and individualized learning activities. Nevertheless, concerns related to the accuracy of AI-generated information, excessive learner dependence, academic integrity, privacy, and the absence of genuine human interaction highlight the continuing importance of professional teacher involvement. The study concludes that the effectiveness of AI in English Language Teaching depends primarily on purposeful pedagogical integration and teacher guidance. Rather than replacing teachers, AI should function as a complementary instructional resource that strengthens teachers’ capabilities while preserving human interaction, professional judgment, motivation, cultural understanding, and meaningful communication as fundamental elements of language education.

.

Hereditary cancer syndromes (i.e. BRCA1/2-breast cancer) represent a small portion of around 6% of the population worldwide with genetic diseases, but their histopathological diagnosis is still difficult. In this paper, we present a clinical decision support system that combines an improved XGBoost classifier with SHapley Additive Explanations (SHAP) to provide high predictive accuracy and interpretable AI (XAI) in breast cancer diagnosis based on nuclear morphological features. The proposed approach employs a five-stage framework, namely: (1) Data collection from the Wisconsin Breast Cancer Diagnostic (WDBC) dataset, (2) missing value treatment by using multiple imputation by chained equations (MICE), (3) feature normalization, (4) biomarker selection using recursive feature elimination with cross validation (RFECV), and (5) class imbalance addressing by synthetic minority over-sampling technique (SMOTE). Hyperparameter tuning was done with Optuna using the Tree-structured Parzen Estimator (TPE) for 300 trials. The XGBoost model, evaluated on a test data consisting of 114 samples (20% of the total 569 samples), attained the highest accuracy of 96% and recall of 97% for class malignant, with a close to perfection ROC AUC of 0.99. SHAP results demonstrated that morphological characteristics (convex points and concavity, in particular) were the most important features, which is in line with histopathological understanding of nuclear alterations in hereditary cancer syndromes. Local waterfall plots ensured case-specific interpretability by breaking down single predictions into additive feature contributions. Although the WDBC dataset does not contain direct labels of genotype, the designed framework acts as a reproducible proof-of-concept for transparent, high-performance diagnosis of breast cancer with potential for application to hereditary syndromes, and veterinary histopathology incorporating appropriate species specific validation.

This study reports on a collection of spiders from Misallatah Nature Reserve and National Park (MNRNP), north western Libya, including five species recorded for the first time in the country. 75 spider samples (13 adult males, 20 adult females, 42 juveniles), comprising 12 families (Agelenidae; Araneidae; Dysderidae; Gnaphosidae; Lycosidae; Palpimanidae; Pisauridae; Philodromidae; Pholcidae; Salticidae; Thomisidae; Zodariidae), 13 genera (Lycosoides Lucas, 1846; Argiope Audouin, 1826; Dysdera Latreille, 1804; Nomisia Dalmas, 1921; Hogna Simon, 1885; Palpimanus Dufour, 1820; Holocnemus Simon, 1873; Aelurillus Simon, 1885; Menemerus Simon, 1868; Plexippus C. L. Koch, 1846; Phlegra Simon, 1876; Bassaniodes Pocock, 1903; Zodarion Walckenaer, 1826) and 13 species (Argiope lobata Pallas, 1772; Dysdera crocata C. L. Koch, 1838; Nomisia recepta Pavesi, 1880; Palpimanus gibbulus Dufour, 1820; Holocnemus pluchei Scopoli, 1763; Plexippus paykulli Audouin, 1826; Bassaniodes lalandei Audouin, 1826; Zodarion pileolonotatum Denis, 1935; Lycosoides flavomaculata Lucas, 1846; Hogna effera O. Pickard-Cambridge, 1872; Aelurillus blandus Simon, 1871; Menemerus taeniatus L. Koch, 1867; Phlegra yaelae Prószyński, 1998) were collected; the last five species are first records in Libya.