Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

In addition to being a novel medication in treating obesity and type 2 diabetes mellitus, tirzepatide is currently being studied to assess its effectiveness and safety on various health parameters, specifically with an emphasis on the neurological field, including sleep medicine and neurodegenerative conditions. In this perspective, we highlight the recent FDA approval of tirzepatide’s use for the treatment of obstructive sleep apnea, with recommendations for future research to extend use in children and adolescents.

Two locally isolated microalgae (Chlorella vulgaris Bejerinck and Nitzschia palea (Kützing) W. Smith) were used in the current study to test their ability to production biodiesel through stimulated in different nitrogen concentration treatments (0, 2, 4, 8 gl ), and effect of nitrogen concentration on the quantity of primary product (carbohydrate, protein ), also the quantity and quality of lipid. The results revealed that starvation of nitrogen led to high lipid yielding, in C. vulgaris and N. palea the lipid content increased from 6.6% to 40% and 40% to 60% of dry weight (DW) respectively.Also in C. vulgaris, the highest carbohydrate was 23% of DW from zero nitrate medium and the highest protein was 50% of DW in the treatment 8gl. Whil

AW Ali T, Journal of the Faculty of Medicine, 2015 - Cited by 3

תקציר :

 המחקר הזה הוא ניסיון לשפוך אור על נושא מרכזי וחשוב בחייהם של היהודים, "הממד הדתי" אצל היהודים, מחקרי הנקרא "הממד הדתי בסיפור העברי המודרני" גם מתייחס להשפעת התרבות הדתית של המספר והחוג המשפחתי שחי בו, ואיך שיקף המספר את כל הדברים האלה ביצירותיו הסיפורית .

המספר בוחר במילים ובמונחים בעלי משמעויות דתיות או מביא את הסיפור הזה אשר קרוב אל נושא הסיפור ההולך באותה מגמה .גם כן השפעת התיאולג

Background: Although they are not life threatening, dental caries and periodontal disease are the most predominant and widely spread oral diseases throughout the world. Another most common dental problem seen in children is dental trauma. The aims of the study included the investigation of the prevalence and severity of dental caries, gingivitis and dental plaque in relation to gender, furthermore, the prevalence and severity of the traumatized anterior teeth were assessed. Materials and Methods: This oral health survey was conducted among primary school children aged 9 years old in Al-Diwaniyah city in Iraq. The total sample composed of 600 child (320 males and 280 females) selected randomly from different school in Al-Diwaniyah city. Dia

To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

The accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l