Quranic Verses Semantic Relatedness Using AraBERT

Bidirectional Encoder Representations from Transformers (BERT) has gained popularity in recent years producing state-of-the-art performances across Natural Language Processing tasks. In this paper, we used AraBERT language model to classify pairs of verses provided by the QurSim dataset to either be semantically related or not. We have pre-processed The QurSim dataset and formed three datasets for comparisons. Also, we have used both versions of AraBERT, which are AraBERTv02 and AraBERTv2, to recognise which version performs the best with the given datasets. The best results was AraBERTv02 with 92% accuracy score using a dataset comprised of label ‘2’ and label '-1’, the latter was generated outside of QurSim dataset

Study and interest of cellular load in respiratory samples for the optimization of molecular virological diagnosis in clinical practice

BACKGROUND: Respiratory viral diagnosis of upper respiratory tract infections has largely developed through multiplex molecular techniques. Although the sensitivity of different types of upper respiratory tract samples seems to be correlated to the number of sampled cells, this link remains largely unexplored. METHODS: Our study included 800 upper respiratory tract specimens of which 400 negative and 400 positive for viral detection in multiplex PCR. All samples were selected and matched for age in these 2 groups. For the positive group, samples were selected for the detected viral species. RESULTS: Among the factors influencing the cellularity were the type of sample (p < 0.0001); patient age (p < 0.001); viral positive or negative nature of the sample (p = 0.002); and, for the positive samples, the number of viral targets detected (0.004 < p < 0.049) and viral species. CONCLUSION: The cellular load of upper respiratory samples is multifactorial and occurs for many in the sensitivity of molecular detection. However it was not possible to determine a minimum cellularity threshold allowing molecular viral detection. The differences according to the type of virus remain to be studied on a larger scale

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS