Online learning environments have become an established presence in higher education in the Kingdom of Saudi Arabia, especially with the expected of Covid-19 pandemic. At present, supporting e-learning with interactive virtual campuses is a future aim in education. In order to solve the problems of the interactivity and the adaptability of e-online learning systems in Saudi universities, this paper proposes a module, based on digital learning, and to be used in learning management systems to meet the challenges a future goal in e-online learning. The e-learning system should be intelligent and has the possibility to inspire the specific characteristics (i.e., metadata) of a student used to access to their social media profiles.

No abstract

BackgroundPapillary Thyroid Carcinoma (PTC) is the most frequent endocrine malignancy with a variety of histological presentations. Warthin-like Papillary Thyroid Carcinoma (WLPTC) is an uncommon neoplasm that is recognized as a distinct subtype of PTC in the WHO classification of thyroid tumors. In this report, we present a novel case of WLPTC in a female patient and provide an in-depth review of the available literature on its clinical, pathological, and therapeutic characteristics.Case presentationA 27-year-old female patient was referred for neck swelling. Ultrasound showed two suspicious thyroid nodules leading to a thyroidectomy. She was diagnosed with intermediate-risk bifocal foci of classic PTC and WLPTC, arising from a background of chronic lymphocytic thyroiditis (CLT). This pT1b(m) N1b M0 malignancy was treated with adjuvant isotopic ablation and suppressive thyroxine therapy. The 1-year outcomes were favorable.Literature reviewIt covered articles published from 1995 to 2022, by searching PubMed and Google Scholar using specific terms. Out of 148 articles reviewed by two authors, 25 relevant articles were selected, including 13 case reports and 12 case series. The study included 150 cases of WLPTC. Data related to clinical presentation, imaging, histological features, management, and outcomes, were extracted. The mean age of diagnosis was 39 years, with a female predominance. The most common clinical presentation was neck swelling. Thyroid autoimmunity was positive in 71.6% of patients. Lymph node metastases were present in 28% of cases, with no reported distant metastases. Overall, the outcomes were favorable.ConclusionWLPTC shares similar clinical and radiological presentations as classic PTC. The hallmark histological features of WLPTC are papillae lined with oncocytic tumor cells with papillary nuclear changes and lymphoid stroma. WLPTC is almost constantly associated with CLT. The management of WLPTC aligns with that of classic PTC with comparable stage and risk category, often resulting in favorable outcomes.

The Kingdom of Saudi Arabia is one of the countries that seek to achieve sustainable development through Vision 2030. The objective of this research is to study the impact of digitization to ensure the competitiveness of the Ha’il region to achieve sustainable development goals. To do this, we applied two techniques in two steps. The first step is based on artificial intelligence through a machine learning technique. The second step is the vector auto-regressive model and impulse response functions. The results show that digitization has a strong impact on the achievement of five sustainable development goals in the Ha’il region. These five priority objectives among 17 goals have been determined by a machine learning technique, each of which is likely to contribute in one way or another to economic, social, and environmental aspects. The results suggest that digitization promotes the acceleration of sustainable development in the Ha’il region. This study is interesting for policymakers in Saudi Arabia to use artificial intelligence and digitalization to achieve economic unification of this region with other regions of the Kingdom.

We present in this paper an automatic summarization technique of Arabic texts, based on RST. We first present a corpus study which enabled us to specify, following empirical observations, a set of relations and rhetorical frames. Then, we present our method to automatically summarize Arabic texts. Finally, we present the architecture of the ARSTResume system. Our method is based on the Rhetorical Structure Theory (Mann, 1988) and uses linguistic knowledge. It relies on three pillars. The first consists in locating the rhetorical relations between the minimal units of the text by applying rhetorical rules. One of these units is the nucleus (the segment necessary to maintain coherence) and the other can be either nucleus or satellite (an optional segment). The second pillar is the representation and the simplification of the RST-tree that represents the source text in hierarchical form. The third pillar is the selection of sentences for the final summary, which takes into account the type of the rhetorical relations chosen for the extract. 2 LINGUISTIC ANALYSIS OF THE STUDY CORPUS An automatic summary requires, as a preliminary step, a linguistic analysis of the corpus (newspaper articles). The main goal of this analysis is to determine the surface linguistic units which represent linguistic markers as well as their corresponding validation markers. These linguistic markers are independent from a particular field and are organized in rhetorical relations.