Students' Perception and Acceptance of e-Learning and e-Evaluation in Higher Education

The COVID-19 pandemic has led to increased use of online resources in educational institutions, making e-learning a necessity. This study aimed to investigate how students from four colleges at Jazan University in Saudi Arabia perceived and accepted e-learning and e-evaluation. Methods: 236 students participated in a cross-sectional study conducted in October 2021. The students completed a well-constructed questionnaire with 22 closed-ended questions divided into five domains. The students rated their answers on a 5-point Likert scale from 1 to 5. To analyze the collected data, the researchers utilized SPSS (v26). Result: Out of the total 236 students who participated in the study, most (30.5%) from the College of Public Health and Tropical Medicine (59.8%) used laptops, while 78% of students had a favorable impression of e-learning. Students' perceptions were focused on whether e-learning and e-evaluation methods helped them understand the study material smoothly and clearly. Among the students, 27% strongly agreed, 25% agreed, 16% were neutral, 11% disagreed, and 11% strongly disagreed. Additionally, 28% of the students strongly agreed, and 34% agreed that exam questions during e-evaluation were appropriate and comprehensive. Although online learning may result in less social contact, a lack of social presence, and difficulties in communication harmonization, e-learning still has some positive effects on students. It is considered a powerful platform, especially during emergencies or for those unable to attend in-person classes to complete their studies. The study has significant implications for higher education institutions, especially during emergencies, where online learning is necessary. Future research can further explore the factors that affect student perceptions and acceptance of elearning and e-evaluation and how to improve them. © 2023, Pakistan Journal of Life and Social Sciences. All Rights Reserved.

The Contagious Nature of SARS-CoV-2 Omicron Variant and Vaccine Efficacy

Since the first coronavirus disease-19 (COVID-19) outbreak, variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have continued to dominate the global population. The repeated waves of emerging variants, each replacing the previous one with a greater rate of transmissibility and mutations, are the primary cause of the global pandemic. Public health concerns dramatically rose when a highly mutated variant, omicron (B.1.1.529) emerged in late 2021. Omicron has more than 50 mutations, and over 30 mutations are in their spike protein that contributes to the virologic characteristics of the variant. Omicron is more contagious than previously reported SARS-CoV-2 strains and can re-infect people who have already contracted other SARS-CoV-2 infections. The variant has acquired a unique immune escape mechanism against monoclonal antibodies and vaccines. Currently, there are no specific therapeutic drugs or vaccines available to prevent omicron infection and sub lineages emergence. The review was designed to search the recent research or literature papers and compile the most pertinent data on the virologic characteristics of the variant of concern. The study reviewed and discussed the present prevalence, infectivity, dominance, immune evasion, therapeutic options, vaccine efficacy, and the future prospect of the omicron variant. Omicron variant has become a global public health concern due to the emergence of highly mutated sub lineages. Developing variant-specific therapeutic drugs or vaccines is desirable to prevent the spread of these contagious variants globally. © 2022, The Running Line. All rights reserved.

Death caused by covid-19 in top ten countries in Asia affected by covid-19 pandemic with special reference to Pakistan.

The COVID-19 is a contagious viral disease, was first emerged in Wuhan, China in December 2019 and became the whole world on alert. The mortality rate in top most countries in Asia with special reference to Pakistan has been focused. Since February 26 to September 2020 the total confirmed cases and mortality rate was measured through Wikipedia and the notable journals. Iran is the only country having highest number of deaths (5.73%) followed by Indonesia (3.77%) while Saudi Arabia shows the lowest number of deaths as 1.39%. In Pakistan the first case was confirmed in 26th February, 2020. The nCov-19 has closely related to severe acute respiratory syndrome (SARS) hence SARS COV-2 was named. This virus is responsible for more than 33.9 million deaths in over all the world as of 20th September, 2020. The number of new cases is increasing time to time. Sindh province of Pakistan has reported the highest number of cases till September, 20, 2020 as compared to other parts of the country and has the highest number of death followed by Khyber Pakhtunkhwa. Because of the person to person contact the disease is spreading rapidly. The individuals who has already infected with other diseases like cancer or diabetic etc. are vulnerable. The nCOV-19 is the most contagious due to its mode of transmission. There is still no vaccine is available for the treatment of disease caused by nCoV-2019. It is therefore the only option to control this pandemic is to adopt effective preventive measures.

Deep Learning Based COVID-19 Detection: Challenges and Future Directions

Coronavirus (COVID-19) is an ecumenical pandemic that has affected the whole world drastically by raising a global calamitous situation. Due to this pernicious disease, millions of people have lost their lives. The scientists are still far from knowing how to tackle the coronavirus due to its multiple mutations found around the globe. Standard testing technique called Polymerase Chain Reaction (PCR) for the clinical diagnosis of COVID-19 is expensive and time consuming. However, to assist specialists and radiologists in COVID-19 detection and diagnosis, deep learning plays an important role. Many research efforts have been done that leverage deep learning techniques and technologies for the identification or categorization of COVID-19 positive patients, and these techniques are proved to be a powerful tool that can automatically detect or diagnose COVID-19 cases. In this paper, we identify significant challenges regarding deep learning-based systems and techniques that use different medical imaging modalities, including Cough and Breadth, Chest X-ray, and Computer Tomography (CT) to combat COVID-19 outbreak. We also pinpoint important research questions for each category of challenges. IEEE

Proposed resilience strategy for higher education institutions post COVID-19

To quickly cope with the COVID-19 pandemic, universities shifted to complete remote delivery. Remote learning is the area of education that concentrates on technology and methods of teaching aimed at delivering to students who are not physically present on individualised bases. This type of delivery is of advantage, when planned. The technology and capabilities to provide comprehensive remote delivery for some degrees do not exist at present time. This article proposes an outline for the required elements of an effective instructional delivery framework that will enable higher-education institutions to meet standards, maintain pedagogical flexibility and to assure quality of the learning outcome of their remote and blended delivery. The above will take place within an overall conceptual design that is capable of effectively handling the new environmental challenges and therefore, will lead to a quality instructional delivery system that can be used in iterative cycles of faculty use and feedback. © 2022 Inderscience Enterprises Ltd.

Acceptance and Perception of Covid-19 Vaccination for Children

Covid-19 vaccine hesitancy and acceptance delay is an unprecedented challenge for concerned authorities. Existing studies lack the investigation about public vaccination acceptance, specifically for children. In this study, we surveyed the adult population in the UK to determine the diversity in public perception and acceptance of Covid-19 vaccination specifically for the children, among different sociodemographic groups. Statistical results and intelligent clustering outcomes indicate significant relationships between sociodemographic diversity and vaccination acceptance for children and their families. Acceptability for children is significantly dependent on ethnicity (p=3.7e-05), age group, and gender, where only 47% of participants show willingness towards children's vaccination. Primary dataset in this study, along with the experimental outcomes, might be useful for public awareness and policy makers towards better preparation for future epidemics as well as working globally to combat the ongoing Covid-19 variations while running effective vaccination campaigns in the identified sociodemographic groups. © 2022 IEEE.

Bipolar picture fuzzy sets and relations with applications

The notions of both the bipolar fuzzy sets and picture fuzzy sets have been studied by many authors, the bipolar picture fuzzy set is the nice combination of these two notions. Basically, the concepts we present in our study are the direct extensions of both the bipolar fuzzy sets and picture fuzzy sets. In this study, we add few more operations and results in the theory of the bipolar picture fuzzy sets. We also initiate the notion of bipolar picture fuzzy relations along with their applications. We present numerous basic operations along with the algebraic sums, bounded sums, algebraic product, bounded difference on bipolar picture fuzzy sets. Different types of distances between two bipolar picture fuzzy sets are also addressed. We provide the application of bipolar picture fuzzy sets towards decision making theory along with its algorithm. Afterward, we introduce different types of bipolar picture fuzzy relations like bipolar picture fuzzy reflexive, symmetric and transitive relations. Subsequently, we introduce the concepts of the bipolar picture fuzzy equivalence relation and partition. We also produce numerous interesting results based on these relations. Finally, we establish the criteria for the detection of covid-19 at the base of bipolar picture fuzzy relations. © 2022, Prince of Songkla University. All rights reserved.

HYDROXYCHLOROQUINE OVERDOSE

SESSION TITLE: Cases of Overdose, OTC, and Illegal Drug Critical Cases Posters SESSION TYPE: Case Report Posters PRESENTED ON: 10/17/2022 12:15 pm - 01:15 pm INTRODUCTION: Hydroxychloroquine (HCQ) is commonly prescribed for the management of connective tissue disorders such as systemic lupus erythematosus and rheumatoid arthritis. Despite its widespread use, there are limited case reports describing HCQ intoxication and management. HCQ toxicity presents predominantly with cardiovascular manifestations, including hypotension, arrhythmias, and QT interval prolongation on electrocardiogram (EKG). Other findings include visual disturbances, altered mental status, and hypokalemia. CASE PRESENTATION: We present the case of a 60-year-old female with a history of rheumatoid arthritis and depression. She presented to the emergency department (ED) after ingesting 10-15 tablets of HCQ 200 mg in a suicide attempt. In the ED, she was noted to be lethargic and tachycardic. EKG revealed sinus tachycardia with a heart rate of 127 beats per minute and prolonged QTc of 680msec. The diagnostic evaluation also revealed hypokalemia with potassium 3.7mmol/l. Initial management in the ED included administration of activated charcoal, potassium supplementation, and intravenous bicarbonate infusion. The patient was admitted to the ICU for monitoring and supportive care. Serum electrolyte panel and EKG were monitored. The patient made an uneventful recovery after 2-3 days. The QT interval normalized, and hypokalemia improved. She was subsequently discharged to an inpatient psychiatric unit. DISCUSSION: Although HQC is commonly prescribed, there is limited data describing overdose. Our case of HCQ overdose presented as changes in mental status, QT interval prolongation, and hypokalemia. Similar findings have been reported in previous case reports. Management includes early gastric decontamination with activated charcoal, potassium supplementation, and supportive care. Intravenous bicarbonate infusion has been utilized for prolonged QT intervals, and benzodiazepines have been used for agitation and sedation. CONCLUSIONS: Although rare, HCQ toxicity can be life-threatening. It is a commonly prescribed agent, and therefore the clinician should be aware of its toxicity profile and management. Reference #1: Bakhsh HT. Hydroxychloroquine Toxicity Management: A Literature Review in COVID-19 Era. J Microsc Ultrastruct. 2020;8(4):136-140. Published 2020 Dec 10. doi:10.4103/JMAU.JMAU_54_20 Reference #2: McKeever R. Chloroquine/hydroxychloroquine overdose. Vis J Emerg Med. 2020;21:100777. doi:10.1016/j.visj.2020.100777 Reference #3: Lebin JA, LeSaint KT. Brief Review of Chloroquine and Hydroxychloroquine Toxicity and Management. West J Emerg Med. 2020;21(4):760-763. Published 2020 Jun 3. doi:10.5811/westjem.2020.5.47810 DISCLOSURES: No relevant relationships by Priyaranjan Kata No relevant relationships by Wajahat Khan No relevant relationships by Pratiksha Singh

PERSISTENT COVID-19 INFECTION IN A PATIENT WITH CASTLEMAN DISEASE

SESSION TITLE: Rare Pulmonary Infections SESSION TYPE: Rapid Fire Case Reports PRESENTED ON: 10/18/2022 01:35 pm - 02:35 pm INTRODUCTION: Castleman's Disease (CD) includes a group of rare and heterogenous lymphoproliferative disorders that share characteristic histopathological features. The etiology of CD is unknown. The condition results in episodic regional lymphadenopathy. Symptoms are driven by episodic cytokine excess. Clinical presentation can include fevers, night sweats, weight loss and fatigue. Life expectancy is not affected, however patients are at risk of developing various other conditions including amyloidosis, cryptogenic organizing pneumonia and lymphoma. COVID-19 is known to have periods of cytokine excess. In severe instances in can lead to cytokine storm, characterized by bilateral pulmonary infiltrates, worsening hypoxemia, and organ failure. We present the case of a 48 year-old female with CD who endured prolonged COVID-19 and cytokine storm. CASE PRESENTATION: A 48-year-old female with CD presented to the emergency department for shortness of breath. Six months prior to admission she had received one dose of the mRNA-1273 (Moderna) vaccine against SARS-CoV-2. Unfortunately, she contracted COVID-19 prior to the second dose. At that time she was hospitalized at a separate institution for COVID-19 and hypoxemia. The patient was treated with systemic glucocorticoids and remdesivir, and subsequently discharged home on supplemental oxygen via nasal cannula at 2 l/min. Unfortunately her respiratory status progressively declined over the following two months. During this time PCR testing for SARS-CoV-2 was positive on multiple occasions. She subsequently presented to our ER for dyspnea and hypoxemia. She once again tested positive by PCR. Inflammatory markers including fibrin degradation products, c-reactive protein and fibrinogen were severely elevated. Chest radiograph revealed bilateral infiltrates. The patient was placed on high flow oxygen and admitted to the ICU. Treatment was initiated with remdesivir, systemic glucocorticoids, and tocilizumab. Unfortunately, she continued to decline and was eventually placed on mechanical ventilation. The patient was then transferred to another institution for evaluation of extracorporeal membrane oxygenation. DISCUSSION: Both CD and COVID-19 are characterized by cytokine excess. Our patient with CD presented with persistent COVID-19. She remained symptomatic for close to six months. Her course was waxing and waning for the first few months and then progressively declined. Multiple PCR tests for SARS-CoV-2 were positive during this interval. We postulate that the proclivity of CD to cytokine excess had a synergistic effect on the inflammatory components of COVID-19 infection. This may have contributed to the protracted infection. CONCLUSIONS: More research is needed in patients with lymphoproliferative disorders and the impact of COVID-19 infection on their outcomes. Reference #1: Van Rhee, Frits, et al. "International, Evidence-Based Consensus Treatment Guidelines for Idiopathic Multicentric Castleman Disease.” American Society of Hematology, American Society of Hematology, 15 Nov. 2018, https://ashpublications.org/blood/article/132/20/2115/39506/International-evidence-based-consensus-treatment. Reference #2: "Castleman Disease: Symptoms, Causes, Treatments and Tests.” Cleveland Clinic, https://my.clevelandclinic.org/health/diseases/17920-castleman-disease. Reference #3: "Castleman Disease.” NORD (National Organization for Rare Disorders), 10 July 2017, https://rarediseases.org/rare-diseases/castlemans-disease/. DISCLOSURES: No relevant relationships by Wajahat Khan No relevant relationships by Nashwa Yosry

Using Artificial Intelligence to Predict Students’ Academic Performance in Blended Learning

University electronic learning (e-learning) has witnessed phenomenal growth, especially in 2020, due to the COVID-19 pandemic. This type of education is significant because it ensures that all students receive the required learning. The statistical evaluations are limited in providing good predictions of the university’s e-learning quality. That is forcing many universities to go to online and blended learning environments. This paper presents an approach of statistical analysis to identify the most common factors that affect the students’ performance and then use artificial neural networks (ANNs) to predict students’ performance within the blended learning environment of Saudi Electronic University (SEU). Accordingly, this dissertation generated a dataset from SEU’s Blackboard learning management system. The student’s performance can be tested using a set of factors: the studying (face-to-face or virtual), percentage of attending live lectures, midterm exam scores, and percentage of solved assessments. The results showed that the four factors are responsible for academic performance. After that, we proposed a new ANN model to predict the students’ performance depending on the four factors. Firefly Algorithm (FFA) was used for training the ANNs. The proposed model’s performance will be evaluated through different statistical tests, such as error functions, statistical hypothesis tests, and ANOVA tests. © 2022 by the authors.

Understanding the Impact of COVID-19 on Indian Wedding Industry

The study aims to examine the impact of COVID-19 on the wedding industry. The nation-wide lockdown has negatively impacted majority of the sectors in the economy, However, the labour-intensive services sector was hit severely, and the wedding industry is one of them. The fear of spreading COVID-19 along with the government restrictions on the number of guests in wedding ceremonies have been the major factors. This led to a severe slowdown in the wedding industry. On an average, 1,000 people gather in urban and 800 people at a rural wedding. Guest restriction to 50 led to a decline value of the business by more than 90%, which ultimately created unemployment issues for the labour working in this sector. In the conclusion, the study suggested some future implications and directions for the wedding industry. © 2022 Institute for Human Development.

COVID-19 Mortality and Morbidity Rate in a Tertiary Care Hospital Swat, Pakistan

Background: Because of the recent outbreak of Covid-19, the globe is now facing a number of difficult challenges. The morbidity and mortality rate varies depending upon numerous factors. Objective: The objective of the study was to find out the mortality and morbidity rate of Covid-19 in a tertiary care hospital of Swat Methodology: This descriptive cross-sectional study was carried out at the Department of Pathology, Swat Teaching Hospital, Swat, Khyber Pakhtunkha Pakistan for duration of one year from April 2020 to March 2021. Nasopharyngeal or Oropharyngeal swabs were taken from all the enrolled patients and sent to the national institute of health Islamabad or swat public health laboratory for the diagnosis of Covid-19. The rate of morbidity and mortality for all the enrolled patients was recorded. All the data analysis was done by using IBM SPSS version 23. Results: In the current study, totally 11609 patients were enrolled. There were 7329 (63.13%) males and 4280 (36.87%) females. The overall morbidity rate of covid-19 was 18.25% (n= 2089) whereas the overall mortality rate was13.16% (n=275) patients. Conclusion: Our study concludes that the rate of morbidity and mortality of covid-19 is high in district Swat Khyber Pakhtunkhwa, Pakistan. The burden of covid-19 was high in males as compared to females and the mortality rate increases with the increase in age. All the people residing in the district Swat should be vaccinated to decrease both the morbidity and mortality rate of covid-19.

Comparison of Subjective and Physiological Stress Levels in Home and Office Work Environments

Work stress can have serious deleterious effects for individuals and society and therefore its management is of great importance. Work environment has been demonstrated as one of the significant factors effecting work stress. Recently, COVID-19 has led to an increased frequency of individuals working in hybrid work environments mainly comprising of home and office environments. The effects these work environments have on individuals’ mental stress is important to understand for both employers and employees so they can mitigate and effectively manage the mental stress. In this paper, we present an intelligent approach to predict the stress occurrences using the physiological data acquired from individuals working in both remote and office locations. Multiple factors are collected related to physiological indicators of stress and subjective performance level. We developed a boosted tree ensemble model which produced binary stress classification accuracy of 99.9%. The statistical outcomes indicate that there is no overall correlation between mental stress and productivity, however there is some indication of mental stress being is influenced by the work environment, the time of day and the day of the week. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The lived experiences of emergency care personnel in the Western Cape, South Africa during the COVID-19 pandemic: A longitudinal hermeneutic phenomenological study.

In March 2020, the World Health Organisation declared COVID-19 a global pandemic. Shortly after the first case of COVID-19 was reported in South Africa, the Western Cape province experienced a rapid growth in the number of cases, establishing it as the epicentre of the disease in South Africa. The aim of this study was to explore emergency care personnel's lived experiences and their perceptions thereof within the context of the COVID-19 pandemic in the Western Cape province. This study followed a longitudinal hermeneutic phenomenological approach. The convenience sample included prehospital and emergency centre medical personnel. Data were collected over a 4-month period using both one-on-one interviews and participant recorded voice recordings. Data were analysed following Ricoeur's theory of interpretation. Four themes were generated during the data analysis: 1) In the beginning, waiting for the unknown; 2) Next, change and adaptation in the workplace; 3) My COVID-19 feelings; 4) Support and connection. Participants discussed the uncertainty associated with responding to an unknown threat and a need to keep up with constant change in an overburdened work environment. Results showed high levels of uncertainty, restriction, fear, anxiety, and exhaustion. Despite these difficulties, participants demonstrated resilience and commitment to caring for patients. A need for support was also highlighted. Results indicated that change, over time, resulted in adaptation to a new way of practising and keeping safe. Healthcare workers experienced intersecting consequences as frontline healthcare workers and members of the public, all of which impacted their well-being. The importance of compassion and encouragement as forms of support was highlighted in the study. Robust and sustained support structures in a time of change, low mood, and exhaustion are essential.

The COVID-19 pandemic: access to relief under social assistance programs by rural households in India

Purpose - This paper aims at analyzing the determinants of access to relief under social assistance programs among rural households during COVID-19 outbreaks in India. Design/methodology/approach - The study is based on the data of COVID-19-Related Shocks Survey, which covered 5,200 rural households across 6 states of India namely Andhra Pradesh, Bihar, Jharkhand, Madhya Pradesh Rajasthan, and Uttar Pradesh. The access to relief has been assessed as relief-in kind (RIK) as a free special package of wheat, rice, and pulses, supplied through the public distribution system;and direct benefit transfer (DBT) in cash under the Pradhan Mantri Kisan Samman Nidhi (PM-KISAN) Yojana and the Pradhan Mantri Jan-Dhan Yojana (PMJDY). The association between demographic profiles of rural households and access to relief has been analyzed using the chi-square test. Further, marginal effects have been estimated to assess the determinants of rural households' access to relief. Findings -The results show a significant association between types of relief vis-a-vis demographic profiles of the rural households. A significant difference in access to relief among rural households is also evident across the states. Further, the analysis of the marginal effects indicates that female-headed households belonging to lower social class, depending on non-agricultural occupation with lower income, belonging to below poverty line families and seeking wage employment, are more likely to access relief as food grains;whereas male respondents with lower age, belonging to lower-income quartile with memberships in Self Help Groups are more likely to access the cash benefit transfers. Practical implications - The COVID-19 pandemic has affected the food security and livelihood of many across the globe, which necessitated provisioning a package of support to everyone, particularly rural poor households. The World Bank undertook the COVID-19-Related Shocks Survey to provide a quick policy response for managing the risk of COVID-19 outbreak effectively. The results of this study provide timely insights for developing an effective relief strategy for rural households during a crisis. Originality/value - There is limited investigation on access to relief by rural households during the COVID-19 outbreaks and factors affecting the access to relief in terms of cash and kind. This study has utilized a reliable data source to analyze the access of relief packages by the rural communities during the coronavirus outbreak.

The Role of Digital Innovation in E-Learning System for Higher Education during COVID 19: A New Insight from Pedagogical Digital Competence

The book chapter highlights the role of key technological drivers such as Information and communication technology (ICT) adoption, social IoT, and artificial intelligence in e-learning system along with the mediating role of pedagogical digital competence, computer self-efficacy, and moderating role of technostress and techno overload during the COVID-19 pandemic in a developing country like Pakistan. A total of 259 data samples were collected through survey questionnaires from the directorate of information technology of HEIs of Pakistan and analyzed using Partial Least Square -Structural Equation Modeling method (PLS-SEM). The results reveal that ICT adoption and social Internet of Things partially had a significant impact on pedagogical digital competence, computer self-efficacy, and e-learning systems. Likewise, ICT adoption has shown a significant impact on pedagogical digital competence, computer self-efficacy, and e-learning systems. The results also demonstrated that pedagogical digital competence mediates a significant relationship between ICT, social IoT, AI, and e-learning system but that computer self-efficacy partially mediates a significant relationship between ICT, social IoT, AI, and e-learning system. In the context of moderate impact, only technostress moderates the relationship between computer self-efficacy and e-learning system. The book chapter elaborated a unique theoretical concept in the context of the adoption of the technology for e-learning systems, such as key technology drivers in name of “ICT adoption, social IoT, artificial intelligence, pedagogical digital competence, computer self-efficacy, technostress, and techno overload, " during the times of the pandemic. These drivers work as a key technology driver’s tool kit in the e-learning system. The consequences of this research strongly suggest important guidelines for artificial intelligence designers, web developers, technology policymakers, information technology instructors, as well as researchers to deeply observe the main theme of distance learning or e-learning educational system, especially in the era of the COVID-19 pandemic in the context of developing countries like Pakistan. © 2022 selection and editorial matter, Muhammad Mujtaba Asad, Fahad Sherwani, Razali Bin Hassan, and Prathamesh Churi;individual chapters, the contributors.

Detecting and Mitigating the Dissemination of Fake News: Challenges and Future Research Opportunities

Fake news is a major threat to democracy (e.g., influencing public opinion), and its impact cannot be understated particularly in our current socially and digitally connected society. Researchers from different disciplines (e.g., computer science, political science, information science, and linguistics) have also studied the dissemination, detection, and mitigation of fake news;however, it remains challenging to detect and prevent the dissemination of fake news in practice. In addition, we emphasize the importance of designing artificial intelligence (AI)-powered systems that are capable of providing detailed, yet user-friendly, explanations of the classification / detection of fake news. Hence, in this article, we systematically survey existing state-of-the-art approaches designed to detect and mitigate the dissemination of fake news, and based on the analysis, we discuss several key challenges and present a potential future research agenda, especially incorporating AI explainable fake news credibility system.