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A significant number of people infected by COVID19 do not get sick immediately but become carriers of the disease. These patients might have a certain incubation period. However, the classical compartmental model, SEIR, was not originally designed for COVID19. We used the simple, commonly used SEIR model to retrospectively analyse the initial pandemic data from Singapore. Here, the SEIR model was combined with the actual published Singapore pandemic data, and the key parameters were determined by maximizing the nonlinear goodness of fit R2 and minimizing the root mean square error. These parameters served for the fast and directional convergence of the parameters of an improved model. To cover the quarantine and asymptomatic variables, the existing SEIR model was extended to an infectious disease model with a greater number of population compartments, and with parameter values that were tuned adaptively by solving the nonlinear dynamics equations over the available pandemic data, as well as referring to previous experience with SARS. The contribution presented in this paper is a new model called the adaptive SEAIRD model; it considers the new characteristics of COVID19 and is therefore applicable to a population including asymptomatic carriers. The predictive value is enhanced by tuning of the optimal parameters, whose values better reflect the current pandemic.

The COVID-19 pandemic spread generated an urgent need for computational systems to model its behavior and support governments and healthcare teams to make proper decisions. There are not many cases of global pandemics in history, and the most recent one has unique characteristics, which are tightly connected to the current society’s lifestyle and beliefs, creating an environment of uncertainty. Because of that, the development of mathematical/computational models to forecast the pandemic behavior since its beginning, i.e., with a restricted amount of data collected, is necessary. This chapter focuses on the analysis of different data mining techniques to allow the pandemic prediction with a small amount of data. A case study is presented considering the data from Wuhan, the Chinese city where the virus was first detected, and the place where the major outbreak occurred. The PNN + CF method (Polynomial Neural Network with Corrective Feedback) is presented as the technique with the best prediction performance. This is a promising method that might be considered in future eventual waves of the current pandemic or event to have a suitable model for future epidemic outbreaks around the world.

There are several techniques to support simulation of time series behavior. In this chapter, the approach will be based on the Composite Monte Carlo (CMC) simulation method. This method is able to model future outcomes of time series under analysis from the available data. The establishment of multiple correlations and causality between the data allows modeling the variables and probabilistic distributions and subsequently obtaining also probabilistic results for time series forecasting. To improve the predictor efficiency, computational intelligence techniques are proposed, including a fuzzy inference system and an Artificial Neural Network architecture. This type of model is suitable to be considered not only for the disease monitoring and compartmental classes, but also for managerial data such as clinical resources, medical and health team allocation, and bed management, which are data related to complex decision-making challenges.

The application of different tools for predicting COVID19 cases spreading has been widely considered during the pandemic. Comparing different approaches is essential to analyze performance and the practical support they can provide for the current pandemic management. This work proposes using the susceptible-exposed-asymptomatic but infectious-symptomatic and infectious-recovered-deceased (SEAIRD) model for different learning models. The first analysis considers an unsupervised prediction, based directly on the epidemiologic compartmental model. After that, two supervised learning models are considered integrating computational intelligence techniques and control engineering: the fuzzy-PID and the wavelet-ANN-PID models. The purpose is to compare different predictor strategies to validate a viable predictive control system for the COVID19 relevant epidemiologic time series. For each model, after setting the initial conditions for each parameter, the prediction performance is calculated based on the presented data. The use of PID controllers is justified to avoid divergence in the system when the learning process is conducted. The wavelet neural network solution is considered here because of its rapid convergence rate. The proposed solutions are dynamic and can be adjusted and corrected in real time, according to the output error. The results are presented in each subsection of the chapter.

A growing focus on God’s mercy and forgiveness emerged in the wake of the recent Pontificates of John Paul II, Benedict XVI, and Francis. Our time with its multiple crises cries for healing, forgiveness, and the experience of God’s mercy. In social, political, and global terms, humanity craves for “lasting peace, born of the marriage of justice and mercy” (John Paul II, 2001, no. 15). The experience of God’s forgiveness, merciful healing and new life has been expressed many times in the Bible. But, theologically, it has never been formulated as directly as in Hosea 11:8, when God’s own heart becomes “turned over”, “converted” following the blaze of his own overwhelming compassion, paving the way for a fundamental spiritual transformation, rooted in forgiveness and mercy, that opens wellsprings of dignity, healing, and new life for all.

This dissertation is an attempt to analyze the twelve selected dreams written or reviewed by St. John Bosco in order to present the notion of an exemplary Salesian. These dreams inspired Don Bosco’s vocation, charism, and dealing with his life’s contingencies and correlate with his pastoral ministry for youth under the social-ecclesiastical context of the nineteenth century. The methodology for this research consists of two approaches: an investigation of their spiritual theology, and Morton T. Kelsey’s approach. In the first part, five dimensions of spiritual theology are explored: (1) the conformity to the truth, (2) the humility and the docility to the Divine will, (3) the discretion and the gravity of seeking the glory of God, (4) the liberty of Spirit with joy, and (5) the guidance of the Spirit. In the latter part, three issues inspired by Kelsey are explored: (1) the personal issue, including the exploration of thought and feeling; (2) the correlation between the dream content and the reality, including images and archetypal symbols associated with experience and memory; (3) the spiritual issue, including one’s openness to God and relation with Him. Through this present research, a model of an exemplary Salesian has been conceptualized, which considers three virtues: health, wisdom, and sanctity. This present study is expected to be beneficial to enhance the faithful’s spirituality. Moreover it is hoped it will provide a healthy stimulus for Salesians to seek to live an excellent Salesian religious life, and to the faithful be devoted Christians in this world as well for the sake of glorifying the Divine mercy

This dissertation is a comprehensive academic examination of the characteristics and complex historical progress within the Pentecostal and Charismatic Movement in Macau Protestant Churches. Since Macau hosted the first Pentecostal and Charismatic missionary, Thomas J. McIntosh, who entered China in 1907, the history of the Pentecostal and Charismatic Movement in Macau lacks a consistent and synthesized research until now. Thus, primary and secondary resources have been analyzed and reconstructed and historically interpreted to gain a better and deeper understanding of the emergence and development of the Pentecostal and Charismatic Movement within Macau’s Protestant Churches from the beginning up to the present day. This academic review makes an important contribution to Macau with respect to its historical development and will fill the gap in knowledge within the Global church history of the Pentecostal and Charismatic Movement. Key Words: Charismatic, Christianity in China, History of Missionaries in China, Macao, Macau, Pentecostalism, Protestant, T. J. McIntosh