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Quality of life in general population before and during pandemic is topic need to be address by researcher in terms of mobility, self-care, usual activities, pain/discomfort and anxiety/depression. The study was carried out among Saudi population. Data were collected from general population using questionnaire during the period from 22 August 2021 to 10th January 2022. As a result, total 214 participants have included in this study. Among them prevalent age group include 40 years (n= 63, 29.4%) shadowed by the age group 25-35 (n= 61, 28.5%) while above 60 years group were least frequent (n= 1, 0.5%). On questioning the applicants whether they were satisfied with their health and how would they rate their quality of life, their answers were as follows: yes, or satisfied (n= 86, 40.2%), very Satisfied (n= 102, 47.7%) Dissatisfied (n= 11, 5.1%) and neither satisfied nor dissatisfied (n= 15, 7%). Due to pandemic, they were rate quality of life very good (n= 94, 43.9%), good (n= 63, 29.4 %) poor (n= 5, 2.3 %) and neither good and nor poor (n= 52, 24.3 %). During pandemic 96 participants feel no change in their weight but 110 participants respond that there is increase in coffee intake during the pandemic. Similarly increased in smoking habits and decrease rate in social activities (n=119,41.4%). The psychosomatic well-being of people has been interrupted by disturbing their social activities during pandemic.
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The manifestation of generating digital visuals through an algorithm is gaining worldwide attention in the graphic design industry. It is a new form of computing that visualizes data input by the designer or collected in the physical environment and turns them into artwork. The generative design of...
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The area of clinical decision support systems (CDSS) is facing a boost in research and development with the increasing amount of data in clinical analysis together with new tools to support patient care. This creates a vibrant and challenging environment for the medical and technical staff. This chapter presents a discussion about the challenges and trends of CDSS considering big data and patient-centered constraints. Two case studies are presented in detail. The first presents the development of a big data and AI classification system for maternal and fetal ambulatory monitoring, composed by different solutions such as the implementation of an Internet of Things sensors and devices network, a fuzzy inference system for emergency alarms, a feature extraction model based on signal processing of the fetal and maternal data, and finally a deep learning classifier with six convolutional layers achieving an F1-score of 0.89 for the case of both maternal and fetal as harmful. The system was designed to support maternal–fetal ambulatory premises in developing countries, where the demand is extremely high and the number of medical specialists is very low. The second case study considered two artificial intelligence approaches to providing efficient prediction of infections for clinical decision support during the COVID-19 pandemic in Brazil. First, LSTM recurrent neural networks were considered with the model achieving R2=0.93 and MAE=40,604.4 in average, while the best, R2=0.9939, was achieved for the time series 3. Second, an open-source framework called H2O AutoML was considered with the “stacked ensemble” approach and presented the best performance followed by XGBoost. Brazil has been one of the most challenging environments during the pandemic and where efficient predictions may be the difference in saving lives. The presentation of such different approaches (ambulatory monitoring and epidemiology data) is important to illustrate the large spectrum of AI tools to support clinical decision-making.
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The adoption of computer-aided diagnosis and treatment systems based on different types of artificial neural networks (ANNs) is already a reality in several hospital and ambulatory premises. This chapter aims to present a discussion focused on the challenges and trends of adopting these computerized systems, highlighting solutions based on different types and approaches of ANN, more specifically, feed-forward, recurrent, and deep convolutional architectures. One section is focused on the application of AI/ANN solutions to support cardiology in different applications, such as the classification of the heart structure and functional behavior based on echocardiography images; the automatic analysis of the heart electric activity based on ECG signals; and the diagnosis support of angiogram images during surgical interventions. Finally, a case study is presented based on the application of a deep learning convolutional network together with a recent technique called transfer learning to detect brain tumors using an MRI images data set. According to the findings, the model has a high degree of specificity (precision of 0.93 and recall of 0.94 for images with no brain tumor) and can be used as a screening tool for images that do not contain a brain tumor. The f1-score for images with brain tumor was 0.93. The results achieved are very promising and the proposed solution may be considered to be used as a computer-aided diagnosis tool based on deep learning convolutional neural networks. Future works will consider other techniques and compare them with the one presented here. With the comprehensive approach and overview of multiple applications, it is valid to conclude that computer-aided diagnosis and treatment systems are important tools to be considered today and will be an essential part of the trend of personalized medicine over the coming years.
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Creativity and collaboration are crucial to learning development in today's fast-paced educational environment. New technology can bridge humans and their natural needs through immersion in digital environments with physical objects. As knowledge and information evolve, digital interactive experienc...
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Macao inhabit a population of 683,100. The birth rate has been dropping while the death rate has risen compared to two years ago. Cemeteries are becoming crowded, and burial spots are demanding. In this case, video calls and social media can be the solution. How about our beloved ancestors? Can we video call them on their memorial days? This paper presents a VR experience of immersing oneself in the 3D VR of the Chapel of St. Michael of Macao to create a peaceful atmosphere for grave mourning. The chapel is also a personal space where we can be truly isolated in serenity. It is a retreat to pray, disconnect, and reconnect to the beloved deaths that may not be buried in an easily accessible location. The authors propose a possible future of mourning our loved ones through virtual reality and telepresence: an immersive experience connected with Macao's extraordinary and cultural unicity.
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Mangrove forests are one of the most ecologically valuable ecosystems in the world and provide a wide variety of ecosystem services to coastal communities, including cities. Macao, a highly urbanized coastal city located on the southern coast of China west of the Pearl River, is home to several species of mangroves with many associated flora and fauna. Mangrove forests in Macao are vulnerable to threats due to pressure from rapid and massive urban developments in the area, which led to mangrove loss in the past decades. To address this issue, the local authorities established special Ecological Zones for the management of the local mangroves. To reinforce local conservation efforts, educating the local population about the value of mangroves, especially school students, is of utmost importance. To evaluate the impact of environmental education activities on the environmental orientation, knowledge, and values of students toward mangrove conservation in Macao, a quasi-experimental study was undertaken. The effectiveness of a mangroves exhibition and field visit were evaluated using the New Environmental Paradigm (NEP) Scale—Macao version in a group of local school students who participated in the activities. Overall, the results provided consistently positive evaluations of the impact of the environmental education program. The strongest improvements were found in the students’ pro-environmental orientations, knowledge about mangroves, and value for environmental protection.
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Listening to children’s voices is still not considered an essential part of education in some schools, including many in Asian countries. The authority of schools and teachers is still highly valued under the continued influence of Confucian Heritage Culture in many Asian schools, including a significant number in Macao. Teachers in international schools in Asian countries often experience some difficulties when communicating with young children because of their low English proficiency and the traditional views supported by many parents who grew up with the Confucian Heritage Culture, which encourages children to be quiet in the classroom to be good listeners. This Action research took fifteen months between two school years, 2018- 2019 and 2019-2020, with two groups of four and five-year-old students in a kindergarten classroom. Documentation posters were created for young children to use the next morning to reflect on their learning. The pedagogy of listening and pedagogical documentation from the Reggio Emilia approach were implemented to discover and record young children’s ideas and interests, work with daily documentation posters, and help them reflect on documentation posters to improve their learning and develop their higher-order thinking skills. Photos and videos, observation notes with the children’s comments, documentation posters, and reflective discussions were used as interventions to collect the children’s ideas and record their learning activities. The children learned to use documentation posters to remember, think, share, and improve their learning. The children’s comments from Learning Centres, recess, and reflective discussions were used to examine their understanding of learning and higher-order thinking skills. During one Pilot Cycle and three structured data collection cycles, the children demonstrated improvement in learning for each learning project and development of their thinking skills both with and without the teacher’s support. The children demonstrated higher-order thinking skills more often from Learning Centres and recess when they had to solve problems. They also demonstrated higher-order thinking skills more often during the whole group reflective discussions than in small group reflections, when a bigger number of children joined or when they had enough time to think. The thinking skills when children were reflecting were observed to concentrate on remembering and understanding as they focused on remembering and sharing the previous day’s work. The children’s other higher-order thinking skills did not show an increase in frequency during reflective discussions. However, the children demonstrated active engagement and a range of higher-order thinking skills when the teacher asked openended questions and provided support and comments to help them to connect their learning to their past experiences. Findings indicated that the children’s learning from each Learning Centre showed change and improvement during their play over time according to their interests, indicated by their material use and comments. The research was limited by its small number of participants within their age group due to convenience sampling and the children’s relatively limited ability to demonstrate higher-order thinking skills. This study has shown how teachers could help children use daily documentation posters to develop their learning and thinking skills by visualizing their ideas and the teacher’s important role in supporting children’s learning with active listening and support in the classroom
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In this chapter, a mathematical model explaining generically the propagation of a pandemic is proposed, helping in this way to identify the fundamental parameters related to the outbreak in general. Three free parameters for the pandemic are identified, which can be finally reduced to only two independent parameters. The model is inspired in the concept of spontaneous symmetry breaking, used normally in quantum field theory, and it provides the possibility of analyzing the complex data of the pandemic in a compact way. Data from 12 different countries are considered and the results presented. The application of nonlinear quantum physics equations to model epidemiologic time series is an innovative and promising approach.
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The doctrine of original sin gives people the impression that the goodness of human nature is under-evaluated in the Christian theological tradition. The Chinese philosopher Mencius is famous for his teaching on the goodness of human nature. Reading Mencius and Thomas Aquinas side by side, this article argues that the Mencian teaching on human nature brings us to affirm the goodness of human nature by recovering the significance of the image of God for the Christian doctrine of human nature. If we seek the goodness of human nature in the possibilities to become good, it is natural to see that even in the fallen state the possibilities of becoming like God remain in human nature imprinted with the image of God. It is open to the culmination of a gradual progression to its perfection.
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The world is perpetually changing, and the COVID-19 pandemic has taught us that the future is full of unforeseen challenges and potentialities. What are the implications of the advancement in technology on education? How are teachers coping with contemporary educational expectations? Is there a need to redesign the learning environment? What is the exact nature of the forces driving such a change? Is there anything we can learn from successful innovations around the globe? The goals of this dissertation include designing a learning/teaching app and redesigning classroom furniture for primary-level education. A design thinking methodology is used, working through the phases of empathizing, defining, ideating, prototyping and testing the two potential designs
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