Social Transformations in India, Myanmar, and Thailand: Volume II: Identity and Grassroots for Democratic: Progress

This book explores the multifaceted obstacles to social change that India, Myanmar and Thailand face, and ways to overcome them. With a collection of essays that identify common challenges and salient features affecting diverse communities, this volume examines topics from subnational and local perspectives across the peripheries. The book argues that identity-based divisions have created a system of oppression and political contention that have led to conflicts of different kinds, and hence serving as the common cause of different social issues. At the same time, such issues have created space for marginalized groups around the world to call for change. The volume recognizes that social transformation comes into being through an active process of deconstructing and reconstructing shared norms and ideas. The contents in this book are thus centered around two focuses: The impacts of identities and grassroots. Both of these aspects are at the heart of each country's transformations towards democracy, peace, justice, and freedom. Under this framework, the chapters cover a diverse range of common issues, such as, minority grievances, gender inequality, ethnic identity, grassroots power in alliance-making towards community peace, recovery and resilience, digital freedom, democracy assistance and communication, and bridging multiple divides. As identity-based cleavages are daily lived experiences for individuals and communities, it requires grassroots initiatives and alliances as well as democratic communication to tackle obstacles at the root. Ultimately, the book convinces readers that social transformations must begin at the individual to communal level and local to national level. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Chinese Normal Students' Satisfaction of Emergency Remote Learning in Higher Education during COVID-19 Pandemic

Despite the widespread use of emergency remote learning (ERL) during the COVID-19 pandemic in higher education, little is known about the determinants of Chinese normal student satisfaction with ERL. This study uses a questionnaire survey method to examine how Chinese normal students' satisfaction with ERL during the COVID-19 pandemic. The results show that Chinese normal students prefer face-to-face teaching to online teaching to some extent. According to the findings, it is important to emphasize students' pre-class preparation, adjust course assessment methods, change teachers' teaching strategies, create a positive teaching environment, boost students' learning confidence, and help them deal with their anxiety during ERL to improve the online course experience for Chinese students at normal universities. © 2023 ACM.

Old Normal, New Normal, or Renewed Normal: How COVID-19 Changed Human Resource Development

This chapter wants to shed light on the consequences that the COVID-19 pandemic had for human resource development (HRD) in organizations and in the labour market. We intend to compare three situations: Old Normal (before February 2020), New Normal (between March 2022 and October 2021), and Renewed Normal (since October 2021). Crucially, in organizations, work was mostly face to face in the Old Normal, remote in the New Normal, and there is a tendency for some hybrid form to be installed in the Renewed Normal. We compare the three phases in terms of four aspects of HRD and within virtual development relations, namely: work environment, competences, training, and skills. The chapter presents results from a literature review in SCOPUS database. We conclude that COVID-19 changed HRD, because technology changed the environment and, therefore, new competences were required. Therefore, a new form of training was also required, which, when in practice, originated new skills. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

The inspiratory activity of respiratory center and respiratory muscles strength after COVID-19.

The respiratory pump that provides pulmonary ventilation includes the respiratory center, peripheral nervous system, chest and respiratory muscles. The aim of this study was to evaluate the activity of the respiratory center and the respiratory muscles strength after COVID-19 (COronaVIrus Disease 2019). Methods. The observational retrospective cross-sectional study included 74 post-COVID-19 patients (56 (76%) men, median age - 48 years). Spirometry, body plethysmography, measurement of lung diffusing capacity (DLCO), maximal inspiratory and expiratory pressures (MIP and MEP), and airway occlusion pressure after 0.1 sec (P0.1) were performed. In addition, dyspnea was assessed in 31 patients using the mMRC scale and muscle strength was assessed in 27 of those patients using MRC Weakness scale. Results. The median time from the COVID-19 onset to pulmonary function tests (PFTs) was 120 days. The total sample was divided into 2 subgroups: 1 - P0.1 <= 0.15 kPa (norm), 2 - > 0.15 kPa. The lung volumes, airway resistance, MIP, and MEP were within normal values in most patients, whereas DLCO was reduced in 59% of cases in both the total sample and the subgroups. Mild dyspnea and a slight decrease in muscle strength were also detected. Statistically significant differences between the subgroups were found in the lung volumes (lower) and airway resistance (higher) in subgroup 2. Correlation analysis revealed moderate negative correlations between P0.1 and ventilation parameters. Conclusion. Measurement of P0.1 is a simple and non-invasive method for assessing pulmonary function. In our study, an increase in P0.1 was detected in 45% of post-COVID-19 cases, possibly due to impaired pulmonary mechanics despite the preserved pulmonary ventilation as well as normal MIP and MEP values.Copyright © Savushkina O.I. et al., 2023.

Medical Image Diagnosis Using Deep Learning Classifiers for COVID-19

COVID-19 and other diseases must be precisely and swiftly classified to minimize disease spread and avoid overburdening the healthcare system. The main purpose of this study is to develop deep-learning classifiers for normal, viral pneumonia, and COVID-19 disorders using CXR pictures. Deep learning image classification algorithms are used to recognize and categorise image data to detect the presence of illnesses. The raw image must be pre-processed since deep neural networks perform the most important aspect of medical image identification, which includes translating the raw image into an intelligible format. The dataset includes three classifications, including normal and viral pneumonia and COVID-19. To aid in quick diagnosis and the proposed models leverage the performance validation of several models, which are summarised in the form of a recall, Fl-score, precision, accuracy, and AUC, to distinguish COVID-19 from other types of pneumonia. When all the deep learning classifiers and performance parameters were analyzed, the ResNetl0lV2 achieved the highest accuracy of COVID-19 classifications is 97.S2%, ResNetl0lV2 had the greatest accuracy of the normal categorization is 92.04% and the Densenet201 had the greatest accuracy of the pneumonia classification is 99.92%. The suggested deep learning system is an excellent choice for clinical use to aid in the COVID-19, normal, and pneumonia processes for diagnosing infections using CXR scans. Furthermore, the suggested approaches provided a realistic technique to implement in real-world practice, assisting medical professionals in diagnosing illnesses from CXR images. © 2023 IEEE.

Philosophy of education in a new key: Who remembers Greta Thunberg? Education and environment after the coronavirus

This paper explores relationships between environment and education after the Covid-19 pandemic through the lens of philosophy of education in a new key developed by Michael Peters and the Philosophy of Education Society of Australasia (PESA). The paper is collectively written by 15 authors who responded to the question: Who remembers Greta Thunberg? Their answers are classified into four main themes and corresponding sections. The first section, ‘As we bake the earth, let's try and bake it from scratch', gathers wider philosophical considerations about the intersection between environment, education, and the pandemic. The second section, ‘Bump in the road or a catalyst for structural change?', looks more closely into issues pertaining to education. The third section, ‘If you choose to fail us, we will never forgive you', focuses to Greta Thunberg's messages and their responses. The last section, ‘Towards a new (educational) normal', explores future scenarios and develops recommendations for critical emancipatory action. The concluding part brings these insights together, showing that resulting synergy between the answers offers much more then the sum of articles' parts. With its ethos of collectivity, interconnectedness, and solidarity, philosophy of education in a new key is a crucial tool for development of post-pandemic (philosophy of) education.

Teachers' Perceptions, Preparations, And Challenges in the Implementation of Limited Face-To-Face Classroom Interaction in the New Normal

Teachers have varied perceptions in the implementation of the limited face-to-face classroom interaction. Being the implementers, teachers go through series of preparations in ensuring its success while adhering to the guidelines imposed by the authorities to safeguard the health of both teachers and students. Varied teaching strategies and coping mechanisms were utilized to cater learners' needs and confront challenges. Challenges will always be part of the teaching-learning process, though teachers went on rigorous preparations in the implementation of the limited face-to-face classroom interaction. However, it does not obstruct teachers' focus to cope with these challenges and to innovate strategies to help students achieve their academic success. It is revealed that teachers' flexibility, optimism, and their commitment to their profession, paired with support from the administration were of great help during the implementation of the limited face-to-face classroom interaction in the new normal.

Onboarding and Socialization Under COVID-19 Crisis: A Knowledge Management Perspective

COVID-19 has contributed to a digitalization of communication, and in many cases a distribution of the workforce in organizations. In turn, this has affected knowledge management practices during the pandemic. In particular, this paper scrutinizes the impact of the COVID-19 pandemic on onboarding practices in a large public organization. The research aimed to investigate employees' perceptions of the onboarding process during the COVID-19 pandemic, and how they expect "the new normal” workday to unfold. A total of nine employees were interviewed in a large public organization. We find that COVID-19 caused a certain degree of detachment from the workplace among the new employees, raised issues regarding communication, knowledge sharing and personal development, but also the uptake of an extensive and lasting use of digital administrative systems. The newcomers emphasize the importance of being physically present at work. The unanimous prediction of the post-COVID-19 work future was more flexibility regarding working at the office versus working from home, and a balance for newcomers between presence and e-learning when being onboarded. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

A Computational Approach for the Characterization of Airborne Pathogen Transmission in Turbulent Molecular Communication Channels

Airborne pathogen transmission mechanisms play a key role in the spread of infectious diseases such as COVID-19. In this work, we propose a computational fluid dynamics (CFD) approach to model and statistically characterize airborne pathogen transmission via pathogen-laden particles in turbulent channels from a molecular communication viewpoint. To this end, turbulent flows induced by coughing and the turbulent dispersion of droplets and aerosols are modeled by using the Reynolds-averaged Navier-Stokes equations coupled with the realizable k-model and the discrete random walk model, respectively. Via simulations realized by a CFD simulator, statistical data for the number of received particles are obtained. These data are post-processed to obtain the statistical characterization of the turbulent effect in the reception and to derive the probability of infection. Our results reveal that the turbulence has an irregular effect on the probability of infection, which shows itself by the multi-modal distribution as a weighted sum of normal and Weibull distributions. Furthermore, it is shown that the turbulent MC channel is characterized via multi-modal, i.e., sum of weighted normal distributions, or stable distributions, depending on the air velocity. Crown

Multivariate count time series segmentation with "sums and shares” and Poisson lognormal mixture models: a comparative study using pedestrian flows within a multimodal transport hub

This paper deals with a clustering approach based on mixture models to analyze multidimensional mobility count time-series data within a multimodal transport hub. These time series are very likely to evolve depending on various periods characterized by strikes, maintenance works, or health measures against the Covid19 pandemic. In addition, exogenous one-off factors, such as concerts and transport disruptions, can also impact mobility. Our approach flexibly detects time segments within which the very noisy count data is synthesized into regular spatio-temporal mobility profiles. At the upper level of the modeling, evolving mixing weights are designed to detect segments properly. At the lower level, segment-specific count regression models take into account correlations between series and overdispersion as well as the impact of exogenous factors. For this purpose, we set up and compare two promising strategies that can address this issue, namely the "sums and shares” and "Poisson log-normal” models. The proposed methodologies are applied to actual data collected within a multimodal transport hub in the Paris region. Ticketing logs and pedestrian counts provided by stereo cameras are considered here. Experiments are carried out to show the ability of the statistical models to highlight mobility patterns within the transport hub. One model is chosen based on its ability to detect the most continuous segments possible while fitting the count time series well. An in-depth analysis of the time segmentation, mobility patterns, and impact of exogenous factors obtained with the chosen model is finally performed. © 2023, Springer-Verlag GmbH Germany, part of Springer Nature.

A Quantitative Analysis of Different Learning Strategies for Senior High School Students in the 'New Normal'

Along with hitting certain regions of the country, the COVID-19 outbreak substantially impacted all academic institutions, prompting the traditional classroom structure to be adjusted immediately. Governments have shifted to a virtual learning environment to alleviate separation from educational activities and boost involvement. The primary objective of this research is to examine the different learning techniques used by senior high school students at a Philippine University when they engage in online learning. This study investigates the underlying pedagogies and instructional designs employed in the production and delivery of online courses. Numerous challenges, including infrastructure and school readiness for a rapid transition to distant education, would develop due to the rapid transformation in education. The researchers employed a descriptive technique in conducting this study and set survey questions to collect data from respondents. The non-probability sampling approach is used in this study, and the results are analyzed using a 5-point Likert scale to determine the mean and standard deviation. The study's results indicate that although students are dissatisfied with the online setting due to its performance differences from the traditional approach, they believe the course material to be fascinating and relevant for the future. It is also indicated that the online learning materials have a significant impact and are convenient to their education. The researchers recommend that institutions arrange asynchronous and synchronous sessions throughout the week and that institutions pay more attention to course design. Finally, students should investigate the school's potential for online instruction. © 2023 IEEE.

A path to new normal of nuclear medicine facilities: Considerations for reopening

The stormy clouds of the coronavirus disease 2019 outbreak caused a rapidly spreading epidemic still hanging over the sphere. Any steps to transition toward a new normal should be guided by health authorities, together with economic and societal considerations. There are various items mainly falling into three classifications, including patient worry, clinical demand, and economic recession. Social distancing, lay-offs, and decreased number of patients with health insurance may lead to a prolonged period to retrieve normalcy. To return to a new normal, an individualized management model should be developed for each laboratory based on staff, instruments, services, crowding, physical space, hospital base unit, or outpatient clinic. Continuous training of different occupational staffs is among the key parameters in maintaining this readiness. The proposed response model should have internal and systemic integrity as well as coherence among the included items in two intra- and inter-unit management categories, namely thinking globally and acting locally.Copyright © 2021 mums.ac.ir All rights reserved.

Bayesian Noise Modelling for State Estimation of the Spread of COVID-19 in Saudi Arabia with Extended Kalman Filters.

The epistemic uncertainty in coronavirus disease (COVID-19) model-based predictions using complex noisy data greatly affects the accuracy of pandemic trend and state estimations. Quantifying the uncertainty of COVID-19 trends caused by different unobserved hidden variables is needed to evaluate the accuracy of the predictions for complex compartmental epidemiological models. A new approach for estimating the measurement noise covariance from real COVID-19 pandemic data has been presented based on the marginal likelihood (Bayesian evidence) for Bayesian model selection of the stochastic part of the Extended Kalman filter (EKF), with a sixth-order nonlinear epidemic model, known as the SEIQRD (Susceptible-Exposed-Infected-Quarantined-Recovered-Dead) compartmental model. This study presents a method for testing the noise covariance in cases of dependence or independence between the infected and death errors, to better understand their impact on the predictive accuracy and reliability of EKF statistical models. The proposed approach is able to reduce the error in the quantity of interest compared to the arbitrarily chosen values in the EKF estimation.

Teaching Experiences of Early Childhood Educators in the New Normal: The Multi-Faceted Endeavor Theory

Early childhood is considered to be the fastest developmental stage in human life and is essential for the formation of the physical, intellectual, social and emotional domains. Early childhood educators are expected to provide quality education to all young learners because of their high impact. However, before the COVID-19 pandemic, moderate to high levels of psychological burnout already existed among early childhood educators (Al-Adwan, Zaid, Al-Khayat, Mohammad, 2017). The outbreak of the COVID-19 pandemic has caused widespread concern globally, posing unprecedented challenges to various parts of society and education, considered one of the most vulnerable sectors (Lansangan & Gonzales, 2020). All the demands, expectations, and other concerns in this new normal have made teaching and learning an important and popular research topic (Sut & So, 2021). However, little is known about the teaching experiences of the early childhood educators. In this study, it sought to generate a theory in the teaching experiences of early childhood educators in the new normal. With this purpose, this paper utilized the deductive axiomatic approach in theory generation following the steps provided by Padua (2012). There are five axioms construed: (1) the teaching experiences of early childhood educators in the new normal echo the educators' process of development in adjusting to environmental changes;(2) the teaching experiences of the early childhood educators in the new normal involve a learning cycle on how to teach during a pandemic;(3) the teaching experiences of the early childhood educators in the new normal cultivate survival behaviors for overcoming personal and occupational challenges;(4) the teaching experiences of the early childhood educators in the new normal emphasize the fundamental roles of educators in supporting the cognitive, social and emotional needs of children and their families;and (5) the teaching experiences of the early childhood educators in the new normal point out the motivation to achieve a goal. From these five axioms, five propositions were formulated: (1) government agencies and academic institutions should provide substantial supports to early childhood educators to adjust with the environmental changes in teaching during this new normal;(2) professional learning communities of early childhood educators should be encouraged to reflect and share on the teaching experiences during the new normal;(3) trainings cultivating survival behaviors for overcoming personal and occupational challenges should be implemented as part of the early childhood education capability enhancement program;(4 teacher-led guidance and counseling activities for parents and children's wellness should be enhanced to support their cognitive, social and emotional needs;and(5) early childhood educators should continue to stay focus and motivated in achieving their goal by giving them opportunities for reflective narratives. With these papers, a multi-faceted Endeavor theory emerged from the classroom experiences of early childhood educators in the new normal. This theory highlights the multiple challenges and struggles early childhood educators experience in teaching in the new normal.

Workplace change within the COVID-19 context: The new (next) normal.

Purpose: This paper aims to investigate the current status of the workplace, its evolution during COVID-19, and the impact of the pandemic on the new (next) normal. This follows previous research about changes in the workplace influenced by the pandemic. Documents, publications, and surveys from numerous sources have been analysed to discover more about the experience of employees and organizations with remote working and the advantages and disadvantages of accessing the workplace during the pandemic and in the new (next) normal. The paper has two objectives, the first of which is to explore some indicators based on available data sources that can help to understand and, in some way, measure the workplace changes in the context of COVID-19. The second is to extend the previous analysis, using the same timeline framework, by studying the workplace during and after COVID-19. Structure: First, the introduction explains the main basis of the research and the principal data sources, outlining what is known, what is new, and the aim of the paper. Then the research methodology is explained, along with the criteria by which the datasets were selected, and the results for the indicators outcomes. Finally, the concluding section highlights the findings obtained, their implications, the limitations of the study, and suggested future lines of research. Findings: The analysis provides insight into to employees' and organizations' experience with remote working and the advantages and disadvantages of accessing the workplace during the pandemic. The indicators identified can allow a better understanding of the environment and, especially, a deeper knowledge of the new normal situation under COVID-19. Discussion: In previous studies, certain strategic categories were identified in the process of reimagining the workplace after COVID-19. Those strategic categories supported the conclusion that there were several common company policies which, translated into practical action, could help in people's engagement with their work. These policies can be summarized as redesigning the physical space of the workplace, work flexibility, family reconciliation, and health security. The study of these policies, based on data analysis, may open up different research paths and allow us to establish models directly related to employee satisfaction. Originality: The paper continues a previous line of research on the situation in the workplace by incorporating certain indicators that allow its measurement and, above all, its evolution over time, especially during the time of the new (next) normal, and by investigating the current status and future evolution of the workplace in the context of the COVID-19 pandemic. The analysis of the data made possible the identification of patterns within the available literature regarding recent events and, especially, their influence on the workplace. This has led to the development of indicators in a range of categories. Practical implications: The revolution initiated by COVID-19 has changed the way companies and employees work, which has involved a constant reinvention of the way they operate and provoked previously unseen actions and profound changes in the workplace. Therefore, the idea of the workplace will never again be what it was expected to be was before COVID-19, and it will be very different from that in the new (next) normal.The strategic categories and their indicators developed here are considered important for people's engagement with their workplaces and organizations. The processes adopted by firms must facilitate the redesign of the workplace in accordance with the new forms of work and not act as a mere copy or transfer of the usual approaches to remote work. Providing answers to the questions involved, and deepening the classifications of the categories we develop, can help us understand how people can be connected with the newest forms of workplaces. Some categories and their associated indicators are relevant in remote work and home office environments created by COVID-19. Given that the research started within a pandemic that has not yet ended, while we now know a lot more, the near-term future is uncertain.

Virtual Preaching: The New Evangelization in the New Normal

The events following the Second Vatican Council have affirmed the advantages of using social communication as a means for evangelization. The Church formally recognized, although not without its dangers, that media can serve as a modern-day "Areopagus" in which the preaching of the Gospel can be amplified. Furthermore, prompted by the needs of the time, the Roman Pontiffs beginning from Paul VI up to the present have called for a "New Evangelization" that would respond to the challenges of secularization by proclaiming the Good News through new and creative means. The unprecedented worldwide disaster brought about by the COVID-19 pandemic has only cemented the use of social communications in the life and liturgy of the Church more permanently. However, this moment of tragedy can be regarded as an opportunity for grace and transformation so that the Gospel can find new life in virtual seeds. Virtual preaching, which employs social communications as its primary tool, is thus an authentic and effective way of New Evangelization in the New Normal.

Experimental Analysis of Power Quality in a Power Substation Used in a Residential and Educational Sector

The article describes the experimental measurements made at a low-voltage residential and educational power substation, in a point of common coupling. Two groups of experiments were carried out, in normal conditions and during the COVID-19 pandemic. Measurements were made using a power quality analyzer and include phase RMS voltages and line currents, total harmonic distortion and unbalance of phase voltages and line currents, neutral current, active, reactive and apparent powers, power factors and displacement power factors, Fresnel diagrams, and harmonic spectra. Measurements indicate significant differences of power quality indicators between the two measurement groups. © 2023 IEEE.

INNOVATIVE UTILIZATION OF VIRTUAL CONFERENCING APPLICATIONS: BASIS FOR NEW TECHNOLOGICAL MANAGEMENT APPROACH

In this fourth industrial revolution of technologies, video conferencing applications are now utilized for online business meetings, online classes, and scientific and experimental purposes engaged in a virtual meeting room due to rigorous cases of coronavirus disease 2019. Several difficulties and technical disruptions were encountered in using the said apps, especially during online classes and business conferences. In connection thereto, this Optimization and Innovative Utilization of Virtual Conferencing Applications dissertation were developed to have a new basis for a technological management approach based on the most commonly used video conferencing applications. The encountered problems, considered factors, and optimization processes were also determined. Descriptive quantitative research was used as methodology, and initial closed-ended questionnaires, evaluation forms with a 4-point Likert scale, interviews, consultations, and testing were the instruments and sources of data. Three hundred one (301) respondents were randomly selected around the Province of Laguna, Philippines, composed of 203 respondents from schools, 78 respondents from companies, and 20 professional evaluators. The developed strategic model was evaluated using 6 out of 8 general characteristics of the ISO/IEC 25010: 2011 system quality model, which includes usability, reliability, performance efficiency, maintainability, compatibility, and security. All data gathered were validated as well as the statistical treatments such as percentage, weighted and composite means, and t-test, which was used to determine the significant difference between the normal and optimized utilization of video conferencing applications. Obtained results revealed that utilizing the developed strategic model was significantly more acceptable and effective rather than the normal utilization of the common apps. The teachers and students and as well as the workers of business enterprises are the beneficiaries of this study to optimize and utilize the said applications for better learning and optimal workflow © 2006-2023 Asian Research Publishing Network (ARPN). All rights reserved

Emotional Labour During the COVID-19 Pandemic—Current Inquiry and Suggested Future Research Directions

The objective of this article is to examine the impact of macro-extreme emotional experience (MEEE) and the new societal norms during the COVID-19 pandemic on health and well-being and their situational consequences on emotional labour of frontline employees. The vast literature on emotional labour in the past has focused on several situational cues, and individual and organizational factors as antecedents. We did a systematic review of available literature on emotional labour, literature on sentiment analysis and emotional experience during the pandemic and analysed COVID-19 related blogs using Natural Language Processing (NLP) in RStudio. At the same time, we attempted to look at the possible intervention of individual factors of MEEEs and social aspects of the new societal norms as antecedents on emotion regulation process and its outcome and propose a conceptual framework for future research on emotional labour under the ‘new normal'. It was concluded that perceived risk, fear and anxiety are extreme emotions that individuals are experiencing during the pandemic. © 2023 XLRI Jamshedpur, School of Business Management & Human Resources.