Showing papers by "University of Jordan published in 2020"
University of Sfax1, University of Münster2, German Center for Neurodegenerative Diseases3, Otto-von-Guericke University Magdeburg4, University of Gafsa5, Rio de Janeiro State University6, University of Twente7, Catholic University of the Sacred Heart8, Estácio S.A.9, American University in the Emirates10, Imam Khomeini International University11, University of Paris12, University of Genoa13, University of Arkansas14, Stanford University15, University of Toulouse16, Assiut University17, Karlsruhe Institute of Technology18, Georgia Southern University19, Government of Extremadura20, University Medical Center Groningen21, University of Ulm22, Yarmouk University23, University of Jordan24, University of Porto25, Loughborough University26, Paris West University Nanterre La Défense27
TL;DR: Results indicate that isolation is a necessary measure to protect public health, but results indicate that it alters physical activity and eating behaviours in a health compromising direction.
Abstract: Background: Public health recommendations and governmental measures during the COVID-19 pandemic have resulted in numerous restrictions on daily living including social distancing, isolation and home confinement. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on health behaviours and lifestyles at home is undefined. Therefore, an international online survey was launched in April 2020, in seven languages, to elucidate the behavioural and lifestyle consequences of COVID-19 restrictions. This report presents the results from the first thousand responders on physical activity (PA) and nutrition behaviours. Methods: Following a structured review of the literature, the “Effects of home Confinement on multiple Lifestyle Behaviours during the COVID-19 outbreak (ECLB-COVID19)” Electronic survey was designed by a steering group of multidisciplinary scientists and academics. The survey was uploaded and shared on the Google online survey platform. Thirty-five research organisations from Europe, North-Africa, Western Asia and the Americas promoted the survey in English, German, French, Arabic, Spanish, Portuguese and Slovenian languages. Questions were presented in a differential format, with questions related to responses “before” and “during” confinement conditions. Results: 1047 replies (54% women) from Asia (36%), Africa (40%), Europe (21%) and other (3%) were included in the analysis. The COVID-19 home confinement had a negative effect on all PA intensity levels (vigorous, moderate, walking and overall). Additionally, daily sitting time increased from 5 to 8 h per day. Food consumption and meal patterns (the type of food, eating out of control, snacks between meals, number of main meals) were more unhealthy during confinement, with only alcohol binge drinking decreasing significantly. Conclusion: While isolation is a necessary measure to protect public health, results indicate that it alters physical activity and eating behaviours in a health compromising direction. A more detailed analysis of survey data will allow for a segregation of these responses in different age groups, countries and other subgroups, which will help develop interventions to mitigate the negative lifestyle behaviours that have manifested during the COVID-19 confinement.
1,275 citations
TL;DR: The findings of this study offer useful suggestions for policy-makers, designers, developers and researchers, which will enable them to get better acquainted with the key aspects of the e-learning system usage successfully during COVID-19 pandemic.
Abstract: The provision and usage of online and e-learning system is becoming the main challenge for many universities during COVID-19 pandemic. E-learning system such as Blackboard has several fantastic features that would be valuable for use during this COVID-19 pandemic. However, the successful usage of e-learning system relies on understanding the adoption factors as well as the main challenges that face the current e-learning systems. There is lack of agreement about the critical challenges and factors that shape the successful usage of e-learning system during COVID-19 pandemic; hence, a clear gap has been identified in the knowledge on the critical challenges and factors of e-learning usage during this pandemic. Therefore, this study aims to explore the critical challenges that face the current e-learning systems and investigate the main factors that support the usage of e-learning system during COVID-19 pandemic. This study employed the interview method using thematic analysis through NVivo software. The interview was conducted with 30 students and 31 experts in e-learning systems at six universities from Jordan and Saudi Arabia. The findings of this study offer useful suggestions for policy-makers, designers, developers and researchers, which will enable them to get better acquainted with the key aspects of the e-learning system usage successfully during COVID-19 pandemic.
586 citations
TL;DR: In this paper, the authors explored the situation of distance e-learning among medical students during their clinical years and identified possible challenges, limitations, satisfaction as well as perspectives for this approach to learning.
Abstract: As COVID-19 has been declared as a pandemic disease by the WHO on March 11th, 2020, the global incidence of COVID-19 disease increased dramatically. In response to the COVID-19 situation, Jordan announced the emergency state on the 19th of March, followed by the curfew on 21 March. All educational institutions have been closed as well as educational activities including clinical medical education have been suspended on the 15th of March. As a result, Distance E-learning emerged as a new method of teaching to maintain the continuity of medical education during the COVID-19 pandemic related closure of educational institutions. Distance E-Learning is defined as using computer technology to deliver training, including technology-supported learning either online, offline, or both. Before this period, distance learning was not considered in Jordanian universities as a modality for education. This study aims to explore the situation of distance E-learning among medical students during their clinical years and to identify possible challenges, limitations, satisfaction as well as perspectives for this approach to learning. This cross-sectional study is based on a questionnaire that was designed and delivered to medical students in their clinical years. For this study, the estimated sample size (n = 588) is derived from the online Raosoft sample size calculator. A total of 652 students have completed the questionnaire, among them, 538 students (82.5%) have participated in distance learning in their medical schools amid COVID-19 pandemic. The overall satisfaction rate in medical distance learning was 26.8%, and it was significantly higher in students with previous experience in distance learning in their medical schools as well as when instructors were actively participating in learning sessions, using multimedia and devoting adequate time for their sessions. The delivery of educational material using synchronous live streaming sessions represented the major modality of teaching and Internet streaming quality and coverage was the main challenge that was reported by 69.1% of students. With advances in technologies and social media, distance learning is a new and rapidly growing approach for undergraduate, postgraduate, and health care providers. It may represent an optimal solution to maintain learning processes in exceptional and emergency situations such as COVID-19 pandemic. Technical and infrastructural resources reported as a major challenge for implementing distance learning, so understanding technological, financial, institutional, educators, and student barriers are essential for the successful implementation of distance learning in medical education.
366 citations
TL;DR: To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—the authors estimated additional population equivalents with UHC effective coverage from 2018 to 2023, and quantified frontiers of U HC effective coverage performance on the basis of pooled health spending per capita.
304 citations
University of Sfax1, Otto-von-Guericke University Magdeburg2, University of Münster3, German Center for Neurodegenerative Diseases4, University of Gafsa5, Rio de Janeiro State University6, University of Twente7, Estácio S.A.8, Canadian University of Dubai9, Imam Khomeini International University10, University of Paris11, University of Genoa12, York University13, Paris West University Nanterre La Défense14, University of Thessaly15, Loughborough University16, Stanford University17, University of Toulouse18, Assiut University19, Karlsruhe Institute of Technology20, Georgia Southern University21, Government of Extremadura22, University Medical Center Groningen23, University of Ulm24, Yarmouk University25, University of Jordan26, University of Porto27, ISCTE – University Institute of Lisbon28, Catholic University of the Sacred Heart29, Józef Piłsudski University of Physical Education in Warsaw30, University of Sousse31, University of Arkansas32, Manouba University33
TL;DR: The preliminary findings elucidate the risk of psychosocial strain during the early COVID-19 home confinement period in 2020 and suggest implementation of national strategies focused on promoting social inclusion through a technology-based solution is strongly suggested.
Abstract: Public health recommendations and governmental measures during the new coronavirus disease (COVID-19) pandemic have enforced numerous restrictions on daily living including social distancing, isolation, and home confinement. While these measures are imperative to mitigate spreading of COVID-19, the impact of these restrictions on psychosocial health is undefined. Therefore, an international online survey was launched in April 2020 to elucidate the behavioral and lifestyle consequences of COVID-19 restrictions. This report presents the preliminary results from more than one thousand responders on social participation and life satisfaction. Methods: Thirty-five research organizations from Europe, North-Africa, Western Asia, and the Americas promoted the survey through their networks to the general society, in 7 languages (English, German, French, Arabic, Spanish, Portuguese, and Slovenian). Questions were presented in a differential format with questions related to responses “before” and “during” confinement conditions. Results: 1047 participations (54% women) from Asia (36%), Africa (40%), Europe (21%), and others (3%) were included in the analysis. Findings revealed psychosocial strain during the enforced COVID-19 home confinement. Large decreases (p < 0.001) in the amount of social activity through family (−58%), friends/neighbors (−44.9%), or entertainment (−46.7%) were triggered by the enforced confinement. These negative effects on social participation were also associated with lower life satisfaction (−30.5%) during the confinement period. Conversely, the social contact score through digital technologies significantly increased (p < 0.001) during the confinement period with more individuals (+24.8%) being socially connected through digital technology. Conclusion: These preliminary findings elucidate the risk of psychosocial strain during the early COVID-19 home confinement period in 2020. Therefore, in order to mitigate the negative psychosocial effects of home confinement, implementation of national strategies focused on promoting social inclusion through a technology-based solution is strongly suggested.
284 citations
TL;DR: In conclusion, Jordanian medical students showed expected level of knowledge about the COVID-19 virus and implemented proper strategies to prevent its spread.
Abstract: The recent coronavirus disease (COVID-19) pandemic is associated with increasing morbidity and mortality and has impacted the lives of the global populations. Human behavior and knowledge assessment during the crisis are critical in the overall efforts to contain the outbreak. To assess knowledge, attitude, perceptions, and precautionary measures toward COVID-19 among a sample of medical students in Jordan. This is a cross-sectional descriptive study conducted between the 16th and 19th of March 2020. Participants were students enrolled in different levels of study at the six medical schools in Jordan. An online questionnaire which was posted on online platforms was used. The questionnaire consisted of four main sections: socio-demographics, sources of information, knowledge attitudes, and precautionary measures regarding COVID-19. Medical students used mostly social media (83.4%) and online search engines (84.8%) as their preferred source of information on COVID-19 and relied less on medical search engines (64.1%). Most students believed that hand shaking (93.7%), kissing (94.7%), exposure to contaminated surfaces (97.4%), and droplet inhalation (91.0%) are the primary mode of transmission but were indecisive regarding airborne transmission with only 41.8% in support. Participants also reported that elderly with chronic illnesses are the most susceptible group for the coronavirus infection (95.0%). As a response to the COVID-19 pandemic more than 80.0% of study participants adopted social isolation strategies, regular hand washing, and enhanced personal hygiene measures as their first line of defense against the virus. In conclusion, Jordanian medical students showed expected level of knowledge about the COVID-19 virus and implemented proper strategies to prevent its spread.
232 citations
TL;DR: An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode and demonstrates that ISSA outperforms all baseline algorithms in terms of fitness values, accuracy, convergence curves, and feature reduction in most of the used datasets.
Abstract: Many fields such as data science, data mining suffered from the rapid growth of data volume and high data dimensionality. The main problems which are faced by these fields include the high computational cost, memory cost, and low accuracy performance. These problems will occur because these fields are mainly used machine learning classifiers. However, machine learning accuracy is affected by the noisy and irrelevant features. In addition, the computational and memory cost of the machine learning is mainly affected by the size of the used datasets. Thus, to solve these problems, feature selection can be used to select optimal subset of features and reduce the data dimensionality. Feature selection represents an important preprocessing step in many intelligent and expert systems such as intrusion detection, disease prediction, and sentiment analysis. An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. Two main improvements were included into the original SSA algorithm to alleviate its drawbacks and adapt it for feature selection problems. The first improvement includes the use of Opposition Based Learning (OBL) at initialization phase of SSA to improve its population diversity in the search space. The second improvement includes the development and use of new Local Search Algorithm with SSA to improve its exploitation. To confirm and validate the performance of the proposed improved SSA (ISSA), ISSA was applied on 18 datasets from UCI repository. In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. In these experiments four different assessment criteria were used. The rdemonstrate that ISSA outperforms all baseline algorithms in terms of fitness values, accuracy, convergence curves, and feature reduction in most of the used datasets. The wrapper feature selection mode can be used in different application areas of expert and intelligent systems and this is confirmed from the obtained results over different types of datasets.
224 citations
TL;DR: A new method to binarize a continuous pigeon inspired optimizer is proposed and compared to the traditional way for binarizing continuous swarm intelligent algorithms.
Abstract: Feature selection plays a vital role in building machine learning models. Irrelevant features in data affect the accuracy of the model and increase the training time needed to build the model. Feature selection is an important process to build Intrusion Detection System (IDS). In this paper, a wrapper feature selection algorithm for IDS is proposed. This algorithm uses the pigeon inspired optimizer to utilize the selection process. A new method to binarize a continuous pigeon inspired optimizer is proposed and compared to the traditional way for binarizing continuous swarm intelligent algorithms. The proposed algorithm was evaluated using three popular datasets: KDDCUP99, NLS-KDD and UNSW-NB15. The proposed algorithm outperformed several feature selection algorithms from state-of-the-art related works in terms of TPR, FPR, accuracy, and F-score. Also, the proposed cosine similarity method for binarizing the algorithm has a faster convergence than the sigmoid method.
206 citations
University of Edinburgh1, Johns Hopkins University2, University of the Witwatersrand3, Centers for Disease Control and Prevention4, Institute of Tropical Medicine Antwerp5, Umeå University6, Yale University7, Aga Khan University8, University of Michigan9, University of Turku10, Universidad del Valle de Guatemala11, Clalit Health Services12, Ben-Gurion University of the Negev13, University of Jordan14, All India Institute of Medical Sciences15, Generalitat Valenciana16, Wellcome Trust17, National Institutes of Health18, Colorado School of Public Health19, Anschutz Medical Campus20, Thailand Ministry of Public Health21, Nagasaki University22, University of Cape Town23
TL;DR: The findings provide new and important evidence for maternal and paediatric influenza immunisation, and should inform future immunisation policy particularly in low-income and lower-middle-income countries.
203 citations
Paris West University Nanterre La Défense1, Otto-von-Guericke University Magdeburg2, German Center for Neurodegenerative Diseases3, University of Sfax4, University of Münster5, University of Gafsa6, Rio de Janeiro State University7, University of Twente8, Catholic University of the Sacred Heart9, Estácio S.A.10, Canadian University of Dubai11, Imam Khomeini International University12, University of Paris13, York University14, University of Genoa15, University of Arkansas16, Stanford University17, University of Toulouse18, University of Thessaly19, Assiut University20, Karlsruhe Institute of Technology21, Loughborough University22, Government of Extremadura23, University Medical Center Groningen24, University of Ulm25, Yarmouk University26, University of Jordan27, University of Porto28, Józef Piłsudski University of Physical Education in Warsaw29, Georgia Southern University30, Qatar Airways31, Manouba University32
TL;DR: The ECLB-COVID19 survey revealed an increased psychosocial strain triggered by the home confinement, and a crisis-oriented interdisciplinary intervention is urgently needed to mitigate this high risk of mental disorders.
Abstract: BACKGROUND: Public health recommendations and government measures during the COVID-19 pandemic have enforced restrictions on daily-living. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on mental health and emotional wellbeing is undefined. Therefore, an international online survey (ECLB-COVID19) was launched on April 6, 2020 in seven languages to elucidate the impact of COVID-19 restrictions on mental health and emotional wellbeing. METHODS: The ECLB-COVID19 electronic survey was designed by a steering group of multidisciplinary scientists, following a structured review of the literature. The survey was uploaded and shared on the Google online-survey-platform and was promoted by thirty-five research organizations from Europe, North-Africa, Western-Asia and the Americas. All participants were asked for their mental wellbeing (SWEMWS) and depressive symptoms (SMFQ) with regard to "during" and "before" home confinement. RESULTS: Analysis was conducted on the first 1047 replies (54% women) from Asia (36%), Africa (40%), Europe (21%) and other (3%). The COVID-19 home confinement had a negative effect on both mental-wellbeing and on mood and feelings. Specifically, a significant decrease (p < .001 and Δ% = 9.4%) in total score of the SWEMWS questionnaire was noted. More individuals (+12.89%) reported a low mental wellbeing "during" compared to "before" home confinement. Furthermore, results from the mood and feelings questionnaire showed a significant increase by 44.9% (p < .001) in SMFQ total score with more people (+10%) showing depressive symptoms "during" compared to "before" home confinement. CONCLUSION: The ECLB-COVID19 survey revealed an increased psychosocial strain triggered by the home confinement. To mitigate this high risk of mental disorders and to foster an Active and Healthy Confinement Lifestyle (AHCL), a crisis-oriented interdisciplinary intervention is urgently needed.
194 citations
TL;DR: In this article, the authors investigate the attitudes of undergraduate students towards their experience with emergency online learning during the first few weeks of the mandatory shift to online learning caused by COVID-19.
TL;DR: This review explores EGFR structure and its mutations, signaling pathway, ligand binding and EGFR dimerization, EGF/EGFR interaction, and the progress in the development of EGFR inhibitors.
Abstract: The epidermal growth factor receptor (EGFR) belongs to the ERBB family of tyrosine kinase receptors. EGFR signaling cascade is a key regulator in cell proliferation, differentiation, division, survival, and cancer development. In this review, the EGFR structure and its mutations, signaling pathway, ligand binding and EGFR dimerization, EGF/EGFR interaction, and the progress in the development of EGFR inhibitors have been explored.
TL;DR: The main findings revealed that the use of social media platforms had a significant positive influence on public health protection against COVID-19 as a pandemic and more research is needed to validate how social media channels can be used to improve health knowledge and adopted healthy behaviors in a cross-cultural context.
Abstract: Background: Despite the growing body of literature examining social media in health contexts, including public health communication, promotion, and surveillance, limited insight has been provided into how the utility of social media may vary depending on the particular public health objectives governing an intervention. For example, the extent to which social media platforms contribute to enhancing public health awareness and prevention during epidemic disease transmission is currently unknown. Doubtlessly, coronavirus disease (COVID-19) represents a great challenge at the global level, aggressively affecting large cities and public gatherings and thereby having substantial impacts on many health care systems worldwide as a result of its rapid spread. Each country has its capacity and reacts according to its perception of threat, economy, health care policy, and the health care system structure. Furthermore, we noted a lack of research focusing on the role of social media campaigns in public health awareness and public protection against the COVID-19 pandemic in Jordan as a developing country.
Objective: The purpose of this study was to examine the influence of social media platforms on public health protection against the COVID-19 pandemic via public health awareness and public health behavioral changes as mediating factors in Jordan.
Methods: A quantitative approach and several social media platforms were used to collect data via web questionnaires in Jordan, and a total of 2555 social media users were sampled. This study used structural equation modeling to analyze and verify the study variables.
Results: The main findings revealed that the use of social media platforms had a significant positive influence on public health protection against COVID-19 as a pandemic. Public health awareness and public health behavioral changes significantly acted as partial mediators in this relationship. Therefore, a better understanding of the effects of the use of social media interventions on public health protection against COVID-19 while taking public health awareness and behavioral changes into account as mediators should be helpful when developing any health promotion strategy plan.
Conclusions: Our findings suggest that the use of social media platforms can positively influence awareness of public health behavioral changes and public protection against COVID-19. Public health authorities may use social media platforms as an effective tool to increase public health awareness through dissemination of brief messages to targeted populations. However, more research is needed to validate how social media channels can be used to improve health knowledge and adoption of healthy behaviors in a cross-cultural context.
Universidade Federal de Santa Maria1, Iowa State University2, Katholieke Universiteit Leuven3, University of Manchester4, South London and Maudsley NHS Foundation Trust5, Medical University of Vienna6, Innsbruck Medical University7, Federal University of Rio Grande do Norte8, Maastricht University9, University of Murcia10, University of Palermo11, University of Technology, Sydney12, Autonomous University of Chile13, University of Jordan14, RMIT University15, Anglia Ruskin University16
TL;DR: Those performing ≥30 min/day of moderate to vigorous or ≥15 min/ day of vigorous physical activity had lower odds of prevalent depressive, anxiety, and co-occurring D&A symptoms and those spending ≥10 h/day sedentary were more likely to have depressive symptoms.
Abstract: This is a cross-sectional study evaluating the associations of self-reported moderate to vigorous physical activity, and sedentary behavior with depressive, anxiety, and co-occurring depressive and anxiety symptoms (D&A) in self-isolating Brazilians during the COVID-19 pandemic. Depressive and anxiety symptoms were collected using the Beck Depression and Anxiety Inventories (BDI and BAI). Among the 937 participants (females=72.3%), those performing ≥30 min/day of moderate to vigorous or ≥15 min/day of vigorous physical activity had lower odds of prevalent depressive, anxiety, and co-occurring D&A symptoms. Those spending ≥10 h/day sedentary were more likely to have depressive symptoms.
TL;DR: A good number of natural products with anti‐corona virus activity are the major constituents of some common dietary supplements, which can be exploited to improve the immunity of the general population in certain epidemics.
Abstract: Several corona viral infections have created serious threats in the last couple of decades claiming the death of thousands of human beings. Recently, corona viral epidemic raised the issue of developing effective antiviral agents at the earliest to prevent further losses. Natural products have always played a crucial role in drug development process against various diseases, which resulted in screening of such agents to combat emergent mutants of corona virus. This review focuses on those natural compounds that showed promising results against corona viruses. Although inhibition of viral replication is often considered as a general mechanism for antiviral activity of most of the natural products, studies have shown that some natural products can interact with key viral proteins that are associated with virulence. In this context, some of the natural products have antiviral activity in the nanomolar concentration (e.g., lycorine, homoharringtonine, silvestrol, ouabain, tylophorine, and 7-methoxycryptopleurine) and could be leads for further drug development on their own or as a template for drug design. In addition, a good number of natural products with anti-corona virus activity are the major constituents of some common dietary supplements, which can be exploited to improve the immunity of the general population in certain epidemics.
01 Aug 2020
TL;DR: A new definition of fuzzy fractional derivative, so-called fuzzy conformable, is proposed and the reproducing kernel Hilbert space method in the conformable emotion is constructed side by side with numerical results, tabulated data, and graphical representations.
Abstract: The aim of this article is to propose a new definition of fuzzy fractional derivative, so-called fuzzy conformable. To this end, we discussed fuzzy conformable fractional integral softly. Meanwhile, uniqueness, existence, and other properties of solutions of certain fuzzy conformable fractional differential equations under strongly generalized differentiability are also utilized. Furthermore, all needed requirements for characterizing solutions by equivalent systems of crisp conformable fractional differential equations are debated. In this orientation, modern trend and new computational algorithm in terms of analytic and approximate conformable solutions are proposed. Finally, the reproducing kernel Hilbert space method in the conformable emotion is constructed side by side with numerical results, tabulated data, and graphical representations.
TL;DR: It is argued that senescence represents a barrier to effective anticancer treatment, and the emerging efforts to identify and exploit agents with senolytic properties as a strategy for elimination of the persistent residual surviving tumor cell population are discussed.
Abstract: For the past two decades, cellular senescence has been recognized as a central component of the tumor cell response to chemotherapy and radiation. Traditionally, this form of senescence, termed Therapy-Induced Senescence (TIS), was linked to extensive nuclear damage precipitated by classical genotoxic chemotherapy. However, a number of other forms of therapy have also been shown to induce senescence in tumor cells independently of direct genomic damage. This review attempts to provide a comprehensive summary of both conventional and targeted anticancer therapeutics that have been shown to induce senescence in vitro and in vivo. Still, the utility of promoting senescence as a therapeutic endpoint remains under debate. Since senescence represents a durable form of growth arrest, it might be argued that senescence is a desirable outcome of cancer therapy. However, accumulating evidence suggesting that cells have the capacity to escape from TIS would support an alternative conclusion, that senescence provides an avenue whereby tumor cells can evade the potentially lethal action of anticancer drugs, allowing the cells to enter a temporary state of dormancy that eventually facilitates disease recurrence, often in a more aggressive state. Furthermore, TIS is now strongly connected to tumor cell remodeling, potentially to tumor dormancy, acquiring more ominous malignant phenotypes and accounts for several untoward adverse effects of cancer therapy. Here, we argue that senescence represents a barrier to effective anticancer treatment, and discuss the emerging efforts to identify and exploit agents with senolytic properties as a strategy for elimination of the persistent residual surviving tumor cell population, with the goal of mitigating the tumor-promoting influence of the senescent cells and to thereby reduce the likelihood of cancer relapse.
TL;DR: Coping self‐efficacy is found to ameliorate the effect of psychological distress on nurses' traumatic experience and warrant intensive efforts from healthcare institutions to provide psychosocial support services for nurses and ongoing efforts to screen them for traumatic and psychological distress symptoms.
Abstract: Purpose Health care professionals, particularly nurses, are considered a vulnerable group to experience acute stress disorder (ASD) and subsequent psychological distress amid COVID-19 pandemic. This study aims to establish the prevalence of acute stress disorder and predictors of psychological distress among Jordanian nurses. Methods A quantitative, cross-sectional, descriptive and comparative design was used. Data were collected using a Web-based survey. A total of 448 Jordanian nurses (73% females) completed and returned the study questionnaire. Results The majority of nurses (64%) are experiencing ASD due to the COVID-19 pandemic and thus are at risk for PTSD predisposition. More than one-third of nurses (41%) are also suffering significant psychological distress. Among our sample, age, ASD and coping self-efficacy significantly predicted psychological distress. More specifically, younger nurses are more prone to experience psychological distress than older ones. While higher scores on ASD showed more resultant psychological distress, coping self-efficacy was a protective factor. Conclusion Given that individuals who suffer from ASD are predisposed to PTSD, follow-up with nurses to screen for PTSD and referral to appropriate psychological services is pivotal. Coping self-efficacy is found to ameliorate the effect of psychological distress on nurses' traumatic experience. Such findings warrant intensive efforts from health care institutions to provide psychosocial support services for nurses and ongoing efforts to screen them for traumatic and psychological distress symptoms. Implications for nursing management Nursing leaders and managers are in the forefront of responding to the unique needs of their workforces during the COVID-19 crisis. They need to implement stress-reduction strategies for nurses through providing consecutive rest days, rotating allocations of complex patients, arranging support services and being accessible to staff. They also need to ensure nurses' personal safety through securing and providing personal safety measures and undertake briefings to ensure their staff's physical and mental well-being, as well as providing referrals to appropriate psychological services.
TL;DR: The main contribution of the proposed method is to detect IoT botnet attacks launched form compromised IoT devices by exploiting the efficiency of a recent swarm intelligence algorithm called Grey Wolf Optimization algorithm (GWO) to optimize the hyperparameters of the OCSVM and at the same time to find the features that best describe the IoT botnets problem.
Abstract: Recently, the number of Internet of Things (IoT) botnet attacks has increased tremendously due to the expansion of online IoT devices which can be easily compromised. Botnets are a common threat that takes advantage of the lack of basic security tools in IoT devices and can perform a series of Distributed Denial of Service (DDoS) attacks. Developing new methods to detect compromised IoT devices is urgent in order to mitigate the negative consequences of these IoT botnets since the existing IoT botnet detection methods still present some issues, such as, relying on labelled data, not being validated with newer botnets, and using very complex machine learning algorithms. Anomaly detection methods are promising for detecting IoT botnet attacks since the amount of available normal data is very large. One of the powerful algorithms that can be used for anomaly detection is One Class Support vector machine (OCSVM). The efficiency of the OCSVM algorithm depends on several factors that greatly affect the classification results such as the subset of features that are used for training OCSVM model, the kernel type, and its hyperparameters. In this paper, a new unsupervised evolutionary IoT botnet detection method is proposed. The main contribution of the proposed method is to detect IoT botnet attacks launched form compromised IoT devices by exploiting the efficiency of a recent swarm intelligence algorithm called Grey Wolf Optimization algorithm (GWO) to optimize the hyperparameters of the OCSVM and at the same time to find the features that best describe the IoT botnet problem. To prove the efficiency of the proposed method, its performance is evaluated using typical anomaly detection evaluation measures over a new version of a real benchmark dataset. The experimental results show that the proposed method outperforms all other algorithms in terms of true positive rate, false positive rate, and G-mean for all IoT device types. Also, it achieves the lowest detection time, while significantly reducing the number of selected features.
TL;DR: A critical review of hand sanitation approaches and products available on the market in light of the scientific evidence available to date is presented and a range of hand sanitisation product formulations are provided to allow for extemporaneous preparations at the community and hospital pharmacies during this urgent crisis.
TL;DR: The false belief that COVID-19 was the result of a global conspiracy could be the consequence of a lower level of knowledge about the virus and could lead to a higher level of anxiety, which should be considered in the awareness tools of various media platforms about the current pandemic.
Abstract: The world has been afflicted heavily by the burden of coronavirus disease 2019 (COVID-19) that overwhelmed health care systems and caused severe economic and educational deficits, in addition to anxiety among the public. The main aim of this study was to evaluate the mutual effects of belief that the pandemic was the result of a conspiracy on knowledge and anxiety levels among students at the University of Jordan (UJ). An electronic-based survey was conducted between 29 March, 2020 and 31 March, 2020. The targeted population involved all undergraduate and postgraduate students from the health, scientific and humanities schools at UJ. Survey sections included 26 items on: socio-demographic information, knowledge and sources of information about the disease, attitude towards the false notion that COVID-19 stemmed from a conspiracy and items to assess the anxiety level among students during the quarantine period. The total number of participants was 1540 students. The mean age of study participants was 22 years and females predominated the study population (n = 1145, 74.4%). The majority of participants perceived the disease as moderately dangerous (n = 1079, 70.1%). Males, Jordanians and participants with lower income were more inclined to feel that COVID-19 is very dangerous. A lower level of knowledge and a higher level of anxiety about COVID-19 were associated with the belief that the disease is part of a conspiracy. Females and participants with lower income were more likely to believe that the disease is related to conspiracy. Belief in conspiracy regarding the origin of COVID-19 was associated with misinformation about the availability of a vaccine and the therapeutic use of antibiotics for COVID-19 treatment. The Ministry of Health in Jordan was the most common source of information about COVID-19 reported by the participants (n = 1018). The false belief that COVID-19 was the result of a global conspiracy could be the consequence of a lower level of knowledge about the virus and could lead to a higher level of anxiety, which should be considered in the awareness tools of various media platforms about the current pandemic.
TL;DR: An in-depth review of existing blockchain-based identity management papers and patents published between May 2017 and January 2020 is provided, which identifies potential research gaps and opportunities that will hopefully help inform future research agenda.
TL;DR: It is argued that the exploitation tendency of WOA is limited and can be considered as one of the main drawbacks of this algorithm, and the exploitative and exploratory capabilities of modified WOA in conjunction with a learning mechanism are improved.
Abstract: Whale optimization algorithm (WOA) is a recent nature-inspired metaheuristic that mimics the cooperative life of humpback whales and their spiral-shaped hunting mechanism. In this research, it is first argued that the exploitation tendency of WOA is limited and can be considered as one of the main drawbacks of this algorithm. In order to mitigate the problems of immature convergence and stagnation problems, the exploitative and exploratory capabilities of modified WOA in conjunction with a learning mechanism are improved. In this regard, the proposed WOA with associative learning approaches is combined with a recent variant of hill climbing local search to further enhance the exploitation process. The improved algorithm is then employed to tackle a wide range of numerical optimization problems. The results are compared with different well-known and novel techniques on multi-dimensional classic problems and new CEC 2017 test suite. The extensive experiments and statistical tests show the superiority of the proposed BMWOA compared to WOA and several well-established algorithms.
TL;DR: This review comprehensively addresses in detail the variations in S protein, its receptor-binding characteristics and detailed structural interactions, the process of cleavage involved in priming, as well as other differences between coronaviruses.
Abstract: The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has recently emerged in China and caused a disease called coronavirus disease 2019 (COVID-19). The virus quickly spread around the world, causing a sustained global outbreak. Although SARS-CoV-2, and other coronaviruses, SARS-CoV and Middle East respiratory syndrome CoV (MERS-CoV) are highly similar genetically and at the protein production level, there are significant differences between them. Research has shown that the structural spike (S) protein plays an important role in the evolution and transmission of SARS-CoV-2. So far, studies have shown that various genes encoding primarily for elements of S protein undergo frequent mutation. We have performed an in-depth review of the literature covering the structural and mutational aspects of S protein in the context of SARS-CoV-2, and compared them with those of SARS-CoV and MERS-CoV. Our analytical approach consisted in an initial genome and transcriptome analysis, followed by primary, secondary and tertiary protein structure analysis. Additionally, we investigated the potential effects of these differences on the S protein binding and interactions to angiotensin-converting enzyme 2 (ACE2), and we established, after extensive analysis of previous research articles, that SARS-CoV-2 and SARS-CoV use different ends/regions in S protein receptor-binding motif (RBM) and different types of interactions for their chief binding with ACE2. These differences may have significant implications on pathogenesis, entry and ability to infect intermediate hosts for these coronaviruses. This review comprehensively addresses in detail the variations in S protein, its receptor-binding characteristics and detailed structural interactions, the process of cleavage involved in priming, as well as other differences between coronaviruses.
TL;DR: This survey details the simulation tools of IoT networks, IoT sensors along with their recent application areas, broad IoT research challenges, as well as in-depth analysis of IoT research history and recommendations that attract current IoT researchers' attention.
TL;DR: This overview will address several issues concerned with the COVID-19 pandemic that directly relate to dental practice in terms of prevention, treatment, and orofacial clinical manifestations.
Abstract: COVID-19 was declared a pandemic by the World Health Organization, with a high fatality rate that may reach 8%. The disease is caused by SARS-CoV-2 which is one of the coronaviruses. Realizing the severity of outcomes associated with this disease and its high rate of transmission, dentists were instructed by regulatory authorities, such as the American Dental Association, to stop providing treatment to dental patients except those who have emergency complaints. This was mainly for protection of dental healthcare personnel, their families, contacts, and their patients from the transmission of virus, and also to preserve the much-needed supplies of personal protective equipment (PPE). Dentists at all times should competently follow cross-infection control protocols, but particularly during this critical time, they should do their best to decide on the emergency cases that are indicated for dental treatment. Dentists should also be updated on how this pandemic is related to their profession in order to be well oriented and prepared. This overview will address several issues concerned with the COVID-19 pandemic that directly relate to dental practice in terms of prevention, treatment, and orofacial clinical manifestations.
TL;DR: Results and analysis show that SVM-based feature selection technique with the proposed binary GWO optimizer with elite-based crossover scheme has enhanced efficacy in dealing with Arabic text classification problems compared to other peers.
Abstract: Text classification is one of the challenging computational tasks in machine learning community due to the increased amounts of natural language text documents available in the electronic forms. In this process, feature selection (FS) is an essential phase because thousands of possible feature sets may be considered in text classification. This paper proposes an enhanced binary grey wolf optimizer (GWO) within a wrapper FS approach to tackle Arabic text classification problems. The proposed binary GWO is utilized to play the role of a wrapper-based feature selection technique. The performance of the proposed method using different learning models, including decision trees, K-nearest neighbour, Naive Bayes, and SVM classifiers, are investigated. Three Arabic public datasets, namely Alwatan, Akhbar-Alkhaleej, and Al-jazeera-News, are utilized to evaluate the efficacy of different BGWO-based wrapper methods. Results and analysis show that SVM-based feature selection technique with the proposed binary GWO optimizer with elite-based crossover scheme has enhanced efficacy in dealing with Arabic text classification problems compared to other peers.
TL;DR: There are various routing techniques, real‐time applications of UAVs which are elaborated in this paper, namely, representative, cooperative, and noncooperative techniques, and collision avoidance techniques which are very important for the obstacle‐free environment.
01 Dec 2020
TL;DR: The MTV approach is introduced to boost the performance of the MTDE and demonstrates its advantages in dealing with problems of different levels of complexity.
Abstract: In this article, an effective metaheuristic algorithm named multi-trial vector-based differential evolution (MTDE) is proposed. The MTDE is distinguished by introducing an adaptive movement step designed based on a new multi-trial vector approach named MTV, which combines different search strategies in the form of trial vector producers (TVPs). In the developed MTV approach, the TVPs are applied on their dedicated subpopulation, which are distributed by a winner-based distribution policy, and share their experiences efficiently by using a life-time archive. The MTV can be deployed by different types of TVPs, particularly, we use the MTV approach in the MTDE algorithm by three TVPs: representative based trial vector producer, local random based trial vector producer, and global best history based trial vector producer. Therefore, this study introduces the MTV approach to boost the performance of the MTDE and demonstrates its advantages in dealing with problems of different levels of complexity. The performance of the proposed MTDE algorithm is evaluated on CEC 2018 benchmark suite which include unimodal, multimodal, hybrid, and composition functions and four complex engineering design problems. The experimental and statistical results are compared with state-of-the-art metaheuristic algorithms: GWO, WOA, SSA, HHO, CoDE, EPSDE, QUATRE, and MKE. The results demonstrate that the MTDE algorithm shows improved performance and benefits from high accuracy of optimal solutions obtained.
TL;DR: An enhanced hybrid metaheuristic approach using grey wolf optimizer and whale optimization algorithm to develop a wrapper-based feature selection method that outperforms other state-of-the-art approaches, significantly.
Abstract: The process of dimensionality reduction is a crucial solution to deal with the dimensionality problem that may be faced when dealing with the majority of machine learning techniques. This paper proposes an enhanced hybrid metaheuristic approach using grey wolf optimizer (GWO) and whale optimization algorithm (WOA) to develop a wrapper-based feature selection method. The main objective of the proposed technique is to alleviate the drawbacks of both algorithms, including immature convergence and stagnation to local optima (LO). The hybridization is done with improvements in the mechanisms of both algorithms. To confirm the stability of the proposed approach, 18 well-known datasets are employed from the UCI repository. Furthermore, the classification accuracy, number of selected features, fitness values, and run time matrices are collected and compared with a set of well-known feature selection approaches in the literature. The results show the superiority of the proposed approach compared with both GWO and WOA. The results also show that the proposed hybrid technique outperforms other state-of-the-art approaches, significantly.