MOHAMED SALEM^1,2, MOHAMMAD EL-METWALLY³, WESAMELDIN SABER^4,*, SALLY NEGM^5,6, ATTALLA EL-KOTT^7.8, YASSER MAZROUA^9,10, ABEER MAKHLOUF¹¹, MAHMOUD MOUSTAFA^7,12

BIOCELL, Vol.46, No.8, pp. 1979-1988, 2022, DOI:10.32604/biocell.2022.019301 - 22 April 2022

Abstract Profound inspection of the life forms on the earth teaches how to be the complexity of interrelationships among the various systems. Because of the emergence of novel viruses all the time and the inadequate of vaccines and antivirals, viral contagions are amongst the most causative diseases affecting people worldwide. Fungi exemplify a massive source of bioactive molecules as, many fungal secondary metabolities like Oxoglyantrypine, Carneic acid F, Scedapin C, Asteltoxin E, Phomanolide, Norquinadoline A and Quinadoline B have antiviral activity. This review deals with how secondary metabolites of fungi can help in the war against More >

Hajer Faris¹, Musaria Karim Mahmood², Osama Ahmad Alomari^3,*, Ashraf Elnagar⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5643-5661, 2022, DOI:10.32604/cmc.2022.026228 - 21 April 2022

Abstract Wireless sensor networks (WSNs) are characterized by their ability to monitor physical or chemical phenomena in a static or dynamic location by collecting data, and transmit it in a collaborative manner to one or more processing centers wirelessly using a routing protocol. Energy dissipation is one of the most challenging issues due to the limited power supply at the sensor node. All routing protocols are large consumers of energy, as they represent the main source of energy cost through data exchange operation. Cluster-based hierarchical routing algorithms are known for their good performance in energy conservation… More >

Ankur Dumka¹, Parag Verma², Rajesh Singh³, Anil Kumar Bisht⁴, Divya Anand^5,6,*, Hani Moaiteq Aljahdali⁷, Irene Delgado Noya^6,8, Silvia Aparicio Obregon^6,9

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6029-6044, 2022, DOI:10.32604/cmc.2022.024698 - 21 April 2022

Abstract Coronavirus (COVID-19) has impacted nearly every person across the globe either in terms of losses of life or as of lockdown. The current coronavirus (COVID-19) pandemic is a rare/special situation where people can express their feelings on Internet-based social networks. Social media is emerging as the biggest platform in recent years where people spend most of their time expressing themselves and their emotions. This research is based on gathering data from Twitter and analyzing the behavior of the people during the COVID-19 lockdown. The research is based on the logic expressed by people in this… More >

Anupam Krishnan¹, Anjana P. Anantharaman^2,*

Molecular & Cellular Biomechanics, Vol.19, No.2, pp. 77-88, 2022, DOI:10.32604/mcb.2022.018369 - 25 March 2022

Abstract Computational Fluid Dynamics has become relevant in the study of hemodynamics, where clinical results are challenging to obtain. This paper discusses a 2-Dimensional transient blood flow analysis through an arterial bifurcation for patients infected with the Coronavirus. The geometry considered is an arterial bifurcation with main stem diameter 3 mm and two outlets. The left outlet (smaller) has a diameter of 1.5 mm and the right outlet (larger), 2 mm. The length of the main stem, left branch and right branch are fixed at 35 mm, 20 mm and 25 mm respectively. Viscosity change that… More >

Waleed A. Alghamdi^1,2, Sami H. Alzahrani³, Saeed S. Shaaban^1,*, Naseem A. Alhujaili²

International Journal of Mental Health Promotion, Vol.24, No.3, pp. 361-373, 2022, DOI:10.32604/ijmhp.2022.017685 - 17 March 2022

Abstract This article examines the stress levels, coping responses, and influence of adaptive and maladaptive coping styles on stress in Saudi Arabia during the COVID-19 pandemic. An online cross-sectional survey was distributed to the attendees of a pandemic-related awareness webinars. The questionnaire assessed demographic and clinical characteristics, coping strategies (the brief COPE inventory), and stress levels (the Perceived Stress Scale). A multivariate linear regression analysis was conducted to assess the predictors of stress. The highest adaptive and maladaptive coping styles were reported for religion and self-distraction. Certain groups were independently more vulnerable to experience stress, including… More >

Kazem Nouri^1,*, Milad Fahimi¹, Leila Torkzadeh¹, Dumitru Baleanu^2,3

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1495-1514, 2022, DOI:10.32604/cmc.2022.024406 - 24 February 2022

Abstract The novel Coronavirus COVID-19 emerged in Wuhan, China in December 2019. COVID-19 has rapidly spread among human populations and other mammals. The outbreak of COVID-19 has become a global challenge. Mathematical models of epidemiological systems enable studying and predicting the potential spread of disease. Modeling and predicting the evolution of COVID-19 epidemics in near real-time is a scientific challenge, this requires a deep understanding of the dynamics of pandemics and the possibility that the diffusion process can be completely random. In this paper, we develop and analyze a model to simulate the Coronavirus transmission dynamics… More >

Saleh Albahli^1,*, Farman Hassan², Ali Javed^2,3, Aun Irtaza^2,4

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 833-849, 2022, DOI:10.32604/cmc.2022.024267 - 24 February 2022

Abstract COVID-19 has become a pandemic, with cases all over the world, with widespread disruption in some countries, such as Italy, US, India, South Korea, and Japan. Early and reliable detection of COVID-19 is mandatory to control the spread of infection. Moreover, prediction of COVID-19 spread in near future is also crucial to better plan for the disease control. For this purpose, we proposed a robust framework for the analysis, prediction, and detection of COVID-19. We make reliable estimates on key pandemic parameters and make predictions on the point of inflection and possible washout time for… More >

Nada M. Mostafa^1,5,#, Muhammad I. Ismail^2,#, Amr M. El-Araby³, Dina M. Bahgat¹, Ahmed M. Elissawy^1,5, Ahmed M. Mostafa⁴, Omayma A. Eldahshan^1,5,*, Abdel Nasser B. Singab^1,5,*

Phyton-International Journal of Experimental Botany, Vol.91, No.5, pp. 1089-1104, 2022, DOI:10.32604/phyton.2022.018239 - 24 January 2022

Abstract Coronaviruses caused an outbreak pandemic disease characterized by a severe acute respiratory distress syndrome leading to the infection of more than 200 million patients and the death of more than 4 million individuals. The primary treatment is either supportive or symptomatic. Natural products have an important role in the development of various drugs. Thus, screening of natural compounds with reported antiviral activities can lead to the discovery of potential inhibitory entities against coronaviruses. In the current study, an in-silico molecular docking experiment was conducted on the effects of some of these natural antiviral phytoconstituents, (e.g.,… More >

V. P. Harshini Raji^*, P. Uma Maheswari

International Journal of Mental Health Promotion, Vol.24, No.2, pp. 189-205, 2022, DOI:10.32604/ijmhp.2022.011865 - 18 January 2022

Abstract India imposed the largest lockdown in the world in response to fight the spread of the Novel Coronavirus disease (COVID-19) from 19 March till 31 May 2020. The onset of the pandemic left the general public feeling psychosocially distressed, helpless, and anxious. The researcher developed a Messenger supported Chatbot, based on the broaden and build model, to cater to the healthy general public to promote positivity and mental well-being. 31 participants between 22 and 45 years old consensually took a pre-test, Chatbot intervention, and post-test. The Chatbot provided guided activities out of which positive affirmations, More >

Ahmed Hamza Osman^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6307-6331, 2022, DOI:10.32604/cmc.2022.024145 - 14 January 2022

Abstract This study presents a model of computer-aided intelligence capable of automatically detecting positive COVID-19 instances for use in regular medical applications. The proposed model is based on an Ensemble boosting Neural Network architecture and can automatically detect discriminatory features on chest X-ray images through Two Step-As clustering algorithm with rich filter families, abstraction and weight-sharing properties. In contrast to the generally used transformational learning approach, the proposed model was trained before and after clustering. The compilation procedure divides the datasets samples and categories into numerous sub-samples and subcategories and then assigns new group labels to… More >