Study of IgG and IgM antibody response afterPfizer mRNA Vaccine first dose in Previously infected with COVID-19and uninfected individuals

The current research aimedto demonstrate the extent such as increase in the rate of immune response to antibodies (IgG, IgM) for people who received the first dose of the Pfizer mRNA vaccine at (1-3) weeks times period and to compare them with people who were not taken for the first dose of the same vaccine and none infected with COVID-19.Also the results appearedsignificant variations in immunoglobulin (IgG) levels (P≤ 0.05) between case (Recipients mRNA vaccination) and control patients, there were. In terms of age and gender, however, there were no significant changes (P≥ 0.05) in immunoglobulin (IgM) levels between case (Recipients mRNA vaccination) and control patients.

The diagnosis of COVID-19 in CT images using hybrid machine learning approaches (CNN & SVM)

The new coronavirus disease (2019) has spread quickly as an acute respiratory distress syndrome (ARDS) among millions of individuals worldwide. Furthermore, the number of COVID-19 checking obtainable in hospitals is very limited as compared to the rising number of infections every day. As an outcome, an automatic detection system must be implemented as a quick diagnostic tool for preventing or reducing the spread of COVID-19 among humans. The present paper aims to propose an automated system by means of a hybrid Deep Learning ("convolutional neural network "(CNN)) and "support vector machine (SVM) " approach for identifying COVID-19 pneumonia-infected patients on the basis of chest computed tomography (746 CT images of "COVID-19" and "non-COVID-19"). The proposed system is composed of three phases. The first, pre-processing phase begins with converting CT images into greyscale level CT images of equal size (256×256). The "contrast limited adaptive histogram equalization" technology is adopted to enhance the intensity levels, and demonstrate the feature of lung tissue. It is also necessary to normalize the division of the image elements by 255 to make the values between 0 and 1, as this will speed up the processing process. The second phase, the CNN (SimpNet model), was applied as a deep feature extraction technique to identify CT samples. The SVM classifier and SoftMax function are employed in the third phase to classify COVID-19 pneumonia-infected patients. Specificity, Sensitivity, "F-score ", Accuracy, and "area under curve" are used as criteria to estimate the efficiency of the classification. The results showed a high accuracy rate of COVID-19 classification which reached (98%) and (99.1%) for CNN-SoftMax and CNN-SVM classifier, respectively in the tested dataset (225 CT images). © The Author 2022. This work is licensed under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) that allows others to share and adapt the material for any purpose (even commercially), in any medium with an acknowledgement of the work's authorship and initial publication in this journal.

Critical review of the relationship between resilience, self-esteem and religiosity among the tabligh during the fight of COVID-19

The paper presents resilience, self-esteem and religiosity approach to handle COVID 19 pandemic in Malaysia by an individual when facing and overcoming adversities. One of the factors that influence resilience in a person is self-esteem. According to Coopersmith, self-esteem is an individual's self-evaluation of the capability, significance, patience, consistency and flexibility in oneself when facing pressure. Individuals with a high degree of self-esteem can appreciate themselves, evaluate themselves well, accept their capabilities and deficiencies as well as the negatives and positives in life while being a responsible person. Individuals should not only think about themselves but also appreciate others and cultivate a healthy relationship with those around them. This attitude builds an individual with a high degree of resilience. According to Coopersmith, some of the aspects of self-esteem are power, significance, virtue and competence. © 2020 Innovare Academics Sciences Pvt. Ltd. All rights reserved.

Critical review of reciting al-quran in restoring the resilience and mental health among quarantined COVID-19 patients

The paper was designed to examine the effect of reciting to the Quran in restoring the based on Resilience and Mental Health among Quarantined Covid-19 Patients. Reciting the Al Quran is a phenomenon that is currently shrouding the people around the world, including Malaysia, during the Covid 29 pandemic. The al- Quran has a unique power in changing an individual's inappropriate behaviour to appropriate behaviour. According to Azarpour, Moraditochaeeb, & Bozorgia, the al-Quran contains various elements needed by humankind, such as religious, social, economic, health, medical, scientific, political and other aspects, as a guide for achieving prosperity in this life and the afterlife, reciting the al-Quran daily showers a person with continuous serenity, which is a very effective therapy for a person facing pressures in life. The al-Quran also provides all the internal and external needs required by a person to face the various challenges in life. Reciting the al-Quran is not only advantageous to a person but listening to recitals can also provide serenity and blessings from Allah S.W.T. © 2020 Innovare Academics Sciences Pvt. Ltd. All rights reserved.