The Combination of Ontology-Driven Conceptual Modeling and Ontology Matching for Building Domain Ontologies: E-Government Case Study

During the last decade, ontology engineering has undoubtedly participated in a lot of beneficial applications in different domains. Nevertheless, ontology development still faces several significant challenges that need to be addressed. This study proposes an enhanced architecture for the ontology development lifecycle. With the help of this architecture, users can complete ontology development tasks since it provides guidance for all key activities, from requirement specification to ontology evaluation. Ontology-driven conceptual modeling (ODCM) and ontology matching serve as the foundation of this architecture. ODCM is defined as the application of ontological ideas from various fields to build engineering objects that improve conceptual modeling. Ontology matching is a promising approach to overcome the semantic heterogeneity challenge between different ontologies. The proposed architecture is applied to e-governance domain, which is one of the online services that gains a great attention worldwide, especially during the coronavirus pandemic. However, residents of Arab countries face numerous obstacles and do not receive the full benefits of e-governance. For these reasons, Egyptian e-government is selected as the suggested case study. The results are encouraging when the produced ontology is compared with 20 existing ontologies from the same domain. On the basis of OntoMetrics, the average values of metrics correlated to accuracy, understandability, cohesion and conciseness lie in the 95th, 95th, 95th and 57th percentiles respectively. The results can be further enhanced by defining more non-inheritance relations and distributing the instances across all classes. © 2022. ISCA

Making it internally persuasive: Analysis of the conspiratorial discourse on COVID-19

This study attempts to generate new insights into the wide spread online and offline conspiratorial discourse on COVID-19. Twofold analytical lens consisted of narrative interrelations framework and content analysis showed how the linguistic resources and conversational such as popular socio-religious discourses, hypothetical narratives, personal narratives, personal mental archives, and interpolated arguments are integrated in the interpretation of intertextual Bases such as Bill Gates' TED talk 2015 (26%);Nematullah Wali's predictions (32%);'End of Days' book by Sylvia Browne (14.9%);and 'The Eyes of Darkness' novel by Dean Koontz (22%) by which the conspiracists in Pakistan construct an internally persuasive discourse promoting conspiracy theories on COVID-19. Several linguistic resources such as mood, modality, topicalization, insinuation, and intertextuality emerged as the main tools of making the conspiracy theories internally persuasive.

Prevalence and early outcome of bronchiectasis as an atypical presentation in COVID-19 patients

Introduction: Bronchiectasis was considered as an uncommon radiological feature of corona virus disease 2019 (COVID-19) infection. The clinical course and outcome of COVID-19 bronchiectasis overlap is still a point for research. The aim of this study was to evaluate the prevalence, course, and outcome of bronchiectasis as an atypical presentation of COVID-19 infection. Methods: A cross-sectional study has been conducted from July 2021 to February 2022 and included 425 COVID-19 swab-positive patients who were examined by high resolution computed tomography of the chest during acute phase (4 weeks) of the infection. Results: Fourteen (3.3%) patients newly developed bronchiectasis-de novo. Patients with de novo bronchiectasis had significantly higher cough score, frequency of colored sputum and mMRC score, respiratory distress (p < 0.001) and respiratory failure (p = 0.02) than patients with no bronchiectasis. They also had the higher frequency of ICU's admission (p = 0.02), need to non-invasive (p = 0.01), and invasive mechanical ventilation (p = < 0.001), duration of mechanical ventilation, ICU's stay and overall hospital stay (p < 0.001). As for the outcome, death rate was also statistically significantly higher among those with De novo bronchiectasis than those without bronchiectasis (p = 0.04). Conclusion: Bronchiectasis is an uncommon presentation among COVID-19 patients. However, bronchiectasis increases disease burden in COVID-19 patients. It may have a negative impact on the outcome.

Adverse Effects of COVID-19 Infection on Pregnant Females Admitted to Zagazig Isolation Hospitals

Background: COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly across the world. As pregnant women are at greater risk of complications, they were advised to take additional precautions as the COVID-19 pandemic unfolded. Objective: The aim of the present study was to provide an efficient and robust local database regarding the maternal and neonatal outcomes for the pregnant cases. Patients and methods: An observational retrospective cohort study included 50 pregnant women, infected with COVID-19. They were admitted to Zagazig Isolation Hospitals during the study period, either aborted or in labor. All women were also subjected to detailed history taking, thorough investigations and medical examination. The patients were monitored during delivery and prior to it, with evaluating the respiratory symptoms. The maternal and neonatal outcomes were assessed. Results: There was statistically significant relation between maternal outcome and duration of ICU stay. There was statistically significant relation between maternal outcome and result of CT chest. There was statistically non-significant relation between maternal outcome and neonatal gender or mode of delivery. There was statistically significant relation between maternal outcome and fetal weight, gestational age (higher with good outcome). There was statistically significant relation between need for NICU admission and fetal weight (lower in babies needed NICU admission). Conclusion: Pregnant women, who are infected with COVID-19 doubly, require extra care. There was currently insufficient evidence on COVID-19 and pregnancy, with the majority of cases occurring late in pregnancy, which poses a really potential danger for the mother and her baby. Keywords. © 2022, Ain Shams University Faculty of Medicine. All rights reserved.

Enhancing the Creativity of Employees in the Education Sector During COVID-19 Pandemic: The Role of Rewards

Employees’ creativity in the education sector has never been more important than the past two years when the global coronavirus disease 2019 (COVID-19) pandemic swept the world. This paper presents a study on employees’ creativity in primary public schools in the Kingdom of Bahrain. The study sheds the light on the role of extrinsic rewards in enhancing employees’ creativity. The findings suggest that extrinsic rewards hinder employees’ creativity for employees’ who are mastery goal-oriented and for employees who have an internal locus and external locus of control. Furthermore, this research finds that the mediating effect of intrinsic motivation and the moderating effect of performance orientation are both insignificant. This study provides clear conditions leading to employees’ creativity;hence it provides multiple theoretical and practical implications that worth consideration. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Survey on using deep learning to detection COVID-19 disease

The spread of COVID-19 disease rapidly worldwide and the increase in deaths are a threat to humanity. This threat prompted researchers in deep learning (DL) to find ways to diagnose COVID-19 from computed tomography (CT) or x-rays. Working deep learning identifies the infection accurately through medical imaging, and the practising radiologist can diagnose the illness. This survey will discuss the reason behind deep learning and the technology used in medical image processing. Exposure to the most common research in the recent period uses deep learning techniques in the medical field. We will then collect research related to diagnosing COVID-19 by using medical images, studying them, discussing the better future suggestion and methods proposed by other researchers. We focus on initial available research that detects COVID-19 by deep learning and sees how they can save time and effort in this field. © 2021 IEEE

Non-hospitalised COVID-19 patients have more frequent long COVID-19 symptoms.

BACKGROUND: Long COVID-19 syndrome refers to the persistence of symptoms for more than 12 weeks after the start of acute symptoms. The pathophysiology of this syndrome is not yet clear.OBJECTIVE: To assess long COVID-19 symptoms in hospitalised and non-hospitalised patients.METHODS: A cross-sectional survey was used. The study included 262 patients who were divided into two groups based on their hospital admission history: 167 (63.7%) were not hospitalised, while 95 (36.3%) were hospitalised.RESULTS: Long-COVID was reported in 157 out of 262 patients (59.9%), and was significantly more frequent in non-hospitalised patients (68.3% vs. 45.3%; P < 0.001). During the acute phase, hospitalised patients had more respiratory symptoms (95.9% vs. 85.6%), while non-hospitalised patients had more neuropsychiatric symptoms (84.4% vs. 69.5%; P < 0.05). Constitutional and neuropsychiatric symptoms were the most frequently reported persistent symptoms in both groups, but all persistent symptoms were more frequent in the non-hospitalised group (P < 0.005).CONCLUSION: Long COVID-19 symptoms affect both hospitalised and non-hospitalised patients. Neuropsychiatric manifestations were the most common persistent COVID-19 symptoms. Rehabilitation and psychotherapy could be advised for all recovered COVID-19 patients. Non-hospitalised COVID-19 patients should be counselled to contact healthcare providers whenever needed.

COVID-19 Pandemic Impacts on Construction Projects

Sponsored by the Claims Avoidance and Resolution Committee of the Construction Institute of the American Society of Civil Engineers (ASCE), this book provides a concise overview of the immediate response of the construction industry to the challenges created by the worldwide COVID-19 outbreak. Topics include time and schedule impacts on projects, financial impacts on projects, and new and evolving regulations. This book will be of interest to field engineers, project managers, and all those involved with claims and construction management.

Study of Stochastic Spread-out of Virus Model Associated with Random parameters

The spread-out of viruses has a great impact on people all over the world. Solving deterministic population models can be useful in understanding the changes results from spreading of virus, these models can be complicated if they are associated with any stochastic random parameters. In the current work, simulation and prediction of the virus behavior will be obtained by using spectral techniques. The stochastic models may be associated with more than one source of randomness, it might be noise or random coefficients or both. Spectral techniques are more efficient than other techniques in solving the stochastic models, for example, Wiener Hermite expansion technique, this technique is used to solve the models associated with noise resulting from different sources. It is helpful in predicting and simulating the behavior of the virus, one of the advantages is having high order of convergence. The statistical properties such as the expectation and the variance are calculated and compared with other techniques. © 2020 IEEE.