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Fast and efficient malaria diagnostics are essential in efforts to detect and treat the disease in a proper time. The standard approach to diagnose malaria is a microscope exam, which is submitted to a subjective interpretation. Thus, the automating of the diagnosis process with the use of an intelligent system capable of recognizing malaria parasites could aid in the early treatment of the disease. Usually, laboratories capture a minimum set of images in low quality using a system of microscopes based on mobile devices. Due to the poor quality of such data, conventional algorithms do not process those images properly. This paper presents the application of deep learning techniques to improve the accuracy of malaria plasmodium detection in the presented context. In order to increase the number of training sets, deep convolutional generative adversarial networks (DCGAN) were used to generate reliable training data that were introduced in our deep learning model to improve accuracy. A total of 6 experiments were performed and a synthesized dataset of 2.200 images was generated by the DCGAN for the training phase. For a real image database with 600 blood smears with malaria plasmodium, the proposed Deep Learning architecture obtained the accuracy of 100% for the plasmodium detection. The results are promising and the solution could be employed to support a mass medical diagnosis system.

This book offers an objective and dispassionate analysis of modern educational architecture allowing us to notice gaps. The fundamental question addressed is whether our education system will embrace knowledge-based society and have the foresight to better prepare future generations. If educators around the world step back for a moment, it is not difficult to notice that unanswered questions about education are looming everywhere. The existent academic literature on education is abundant and embracing. In consequence, one can ask why is this book necessary? Indeed, this book is the result of senior university professors sharing their learnings and anticipating the pivotal issues facing all education professionals. According to the United Nations, by 2050, 68% of the world’s population will be living in urban areas. This fact cannot be ignored as it is one of the drivers of the profile of the future students. The reasons to organize this publication are many, but among them three stand out which also function as the driving forces behind this project: (1) University professors teach future generations based on models grounded on knowledge advanced by past experiences; (2) The decisive requirement to understand the needs of the new generations of university millennial students; and (3) What are the critical challenges of global societies? "This book problematizes the issues concerning education, and its main contribution is to answer the need to rethink education, face contemporary challenges, and reorganize the way public policies address education. It critically analyses the challenges of global societies in a decentralized perspective, not only reflecting a western perspective of education and knowledge production. The project's originality comes from the contemporaneity of the topics covered, from the interdisciplinary perspective, and from the specific attention given to trends around education." —Cátia Miriam Costa, Researcher and Invited Assistant Professor, Centre for International Studies, Perfil Ciência

Macao is well known for its gaming industry. However, there are also many traditional small-to-medium enterprises which are family-owned and run. There is no doubt that social capital is one of the key competitive advantages that family businesses possess, particularly when it comes to Chinese businesses with strong family values that emphasize the importance of trustworthiness and guanxi (relationships). As opposed to other forms of capital, social capital cannot be passed from one generation to another through the will of the incumbents. So, how is social capital passed on in family businesses from one generation to the next? Based on an in-depth study of five cases of successful family businesses in Macao, this research identified the forms of social capital present in business families and the succession process of these firms. From the generalizations drawn from the five cases, a theoretical framework is proposed to understand the intergenerational transmission of social capital in Chinese family businesses

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

In the light of the many kinds of journeys that have been considered pilgrimages, this book uses phenomenology as a method to examine the claim that pilgrimage is a journey to the ‘center’ during which pilgrims seek meaning s for themselves. First, by analyzing a phenomenology of Christian pilgrimage, this work attempts to identify what commonalities, as well as differences, exist between Christian pilgrimage and secular pilgrimage in terms of ‘natural attitude’. Next, by using a phenomenological method, such as transcendental reduction, the distinction between these two types of pilgrimage could be clarified that the happiness sought in Christian pilgrimage is both intentionally spiritual and sustainable, while primarily intellectual or sensory in secular pilgrimage. Lastly, this work seeks to establish whether or not ‘being at leisure’ is the primary element for pilgrims whose aim is to attain an understanding of happiness during a pilgrimage

<abstract><p>About 6.5 million people are infected with Chagas disease (CD) globally, and WHO estimates that $ &gt; million people worldwide suffer from ChHD. Sudden cardiac death (SCD) represents one of the leading causes of death worldwide and affects approximately 65% of ChHD patients at a rate of 24 per 1000 patient-years, much greater than the SCD rate in the general population. Its occurrence in the specific context of ChHD needs to be better exploited. This paper provides the first evidence supporting the use of machine learning (ML) methods within non-invasive tests: patients' clinical data and cardiac restitution metrics (CRM) features extracted from ECG-Holter recordings as an adjunct in the SCD risk assessment in ChHD. The feature selection (FS) flows evaluated 5 different groups of attributes formed from patients' clinical and physiological data to identify relevant attributes among 57 features reported by 315 patients at HUCFF-UFRJ. The FS flow with FS techniques (variance, ANOVA, and recursive feature elimination) and Naive Bayes (NB) model achieved the best classification performance with 90.63% recall (sensitivity) and 80.55% AUC. The initial feature set is reduced to a subset of 13 features (4 Classification; 1 Treatment; 1 CRM; and 7 Heart Tests). The proposed method represents an intelligent diagnostic support system that predicts the high risk of SCD in ChHD patients and highlights the clinical and CRM data that most strongly impact the final outcome.</p></abstract>

Nowadays, the increasing number of medical diagnostic data and clinical data provide more complementary references for doctors to make diagnosis to patients. For example, with medical data, such as electrocardiography (ECG), machine learning algorithms can be used to identify and diagnose heart disease to reduce the workload of doctors. However, ECG data is always exposed to various kinds of noise and interference in reality, and medical diagnostics only based on one-dimensional ECG data is not trustable enough. By extracting new features from other types of medical data, we can implement enhanced recognition methods, called multimodal learning. Multimodal learning helps models to process data from a range of different sources, eliminate the requirement for training each single learning modality, and improve the robustness of models with the diversity of data. Growing number of articles in recent years have been devoted to investigating how to extract data from different sources and build accurate multimodal machine learning models, or deep learning models for medical diagnostics. This paper reviews and summarizes several recent papers that dealing with multimodal machine learning in disease detection, and identify topics for future research.

Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool for the accurate detection of COVID-19. The found papers showed high accuracy rate results, ranging between 85.70% and 100%, and F1-Scores from 89.52% to 100%. With this state-of-the-art, we concluded that the models proposed for the detection of COVID-19 already have significant results, but the area still has room for improvement, given the vast symptomatology and the better comprehension of individuals’ evolution of the disease.

Robotics are being used in the intervention with children with Autism Spectrum Disorder (ASD) in many places and already for many years. Many robots were developed and different studies are being made in order to evaluate its effectiveness. “Socially Assistive Robotics” is shown to be effective in different areas mainly in social and emotional development. Milo, a robot developed by a team led by Richard Margolin for the Robots4Autism program (RoboKind, 2020), is one of the robots whose use is reported to be successful. In Macao there is no report of studies or experiences on the use of robots in the intervention with children with ASD. In a collaboration between the Macao Science Centre, the Macao Autism Association (MAA) and the University of Saint Joseph, an exploratory study was developed to understand the applicability of Milo to the work with children with ASD in Macao. The study showed that the robot is able to facilitate social and emotional competences of children with ASD. However, several limitations including language, cultural differences, the inexperienced facilitators and the level of sessions are too simple for the participants to be aware of that may affect the effectiveness of the intervention. It is important to show that the adoption of Milo in Macao for intervening children with ASD can be further implemented, with better practical solutions.

The main focus of this thesis was to characterize the patient information leaftlets as a text genre in Portugal, compare it with the same text genre in other countries and propose a new form of elaborating these documents in order to rise its comprehensibility levels. Therefore, we proceeded with an analysis of the patient information leaflet as a text genre and its relationship with text linguistics and translation. We also analyzed a corpus of 50 patient information leaflets with focus not only on its content, but also in the way they were created. In order to know the opinion of the general public, a survey about the situation of these documents in Portugal was distributed. In order to find the differences between these documents in different contexts, we made a comparison of a portuguese leaflet with leaflets from other countries. By last, we proposed a new writing scheme for these documents, reformulating one of the leaflets analyzed in the corpus and, to get the opinion of the general public, distributing a survey where the reformulated version was compared to the original one. The results point out to a lack of uniformity between documents and the way that they are created in pharmaceutical companies. The content of the patient informations leaflets in Portugal has an excess of text, technical language and a visual organization that is not appealing, problems that were also pointed out by the public in a survey. In the comparison between leaflets of different countries, big differences were found even when they were produced by the same company. When confronted with the original version and the reformulated version of the same document, the general public prefered the latter.

Objective: As a world tourist destination, Macao is inevitably under the impact of the COVID-19 pandemic. However, the market of integrated resorts in Macao are shared by only a few casino concessionaries, together forming an oligopoly. While the firms attempted to adjust price, quantity and quality of their hotel services in response to the pandemic, they could not overlook the strategic interactions with other players in the market. Hence, this paper aims to investigate the possible impact of the pandemic on the oligopolistic strategies in the integrated resort market in Macao. Methodology: Application of a theoretical model of differentiated oligopoly to this six-firm case shows that price differences across firms depend on their quality differentiation. In order to analyze these price differences empirically, this paper collects data of hotel room rates of the integrated resorts from November, 2019 to mid-August, 2020, covering the periods before and after the outbreak of COVID-19. Originality: In the existing literature, there is a lack of studies of the oligopoly in the hospitality industry of Macao. Furthermore, the effect of COVID-19 is still ongoing, so this present paper is one of the first to perform such analysis. Results: The regression of each of the hotel price differentials on the COVID-19 dummy variable shows that COVID-19 has statistically significant impacts on almost all the price differentials. Intuitively, MGM and Wynn were in the high-price segment before and after the outbreak, while other firms switched positions in the low-price segment during the pandemic. One obvious downstream movement was by Conrad. According to the proposition derived from the theory, these imply that COVID-19 should have significant impact on the quality differentiation of the firms. Practical implications: The results are in line with the observations that the integrated resorts have rolled out staycation packages according to preferences of local residents. These quality adjustments observed in Macao’s hospitality industry currently only involved variable inputs rather than fixed inputs of production; therefore, the impact of COVID-19 should be seen as short-term effects. Keywords: Covid-19; Differentiated oligopoly; Hospitality industry; Hotel room rate; Oligopolistic market structure; Pricing strategy.

This paper aimed to build up the theorical and conceptual understanding of future forecasting study of Macau’s GDP and Gross Gaming Revenue (GGR) by co-movement of economic indicators. Macau GDP and GGR showed co-movements with a number of time series economic indicators, including China’s exports and imports, China’s manufacturing PMI, non-manufacturing PMI, China's electricity production growth, share price of some Macau’s gaming operators, etc. These time series data can be found in statistics departments of China, Macau and Hong Kong, stock exchanges, and international organizations such as the International Monetary Fund (IMF), the World Bank, the World Trade Organization (WTO). Burns and Mitchell’s study in 1946 identified co-movements between economic indicators and being further carried out and developed leading, coincident and lagging indicators, which is essential for future econometric models and nowcasting techniques developments to study these co-movements. In particular, with the proper application of nowcasting techniques, future studies can exploit the data of leading and coincident economic indicators to forecast Macau’s GDP and GGR within an acceptable level of error. Since Macau is a “monotown,” where the gaming revenue makes a significant contribution to the economy. The forecasting of gaming revenue is crucial as it aids the gambling and tourism industries in preparing supply and provides information to policymakers to plan for the near future. This research also contributes to understand Macau’s economy by investigating its internal and external economic variables.

YouTube has become increasingly popular for marketing purposes. As corporate and user-generated content is widely available on this platform, beauty-related professionals need to understand how to create videos that make their products more appealing and stand out from the clutter. In this study, we examine four factors (i.e., perceived usefulness of the information, perceived credibility of the information, attitude toward the purchase, and perceived video characteristics) that affect the purchase intentions of female consumers. After viewing beauty-related videos, a sample of 204 female consumers was analyzed by structural equation modeling. The findings showed that videos with more views, likes, and comments tend to have a greater effect on the respondents' intentions to purchase. Also, the factors of perceived usefulness of the information, perceived credibility of the information, and attitude toward the purchase exhibited a significant effect on the intention to buy beauty-related products. The result showed that perceived video characteristics (such as quality and visuals) did not significantly influence the purchase intention, however, there is evidence that this factor should not be ignored by content creators. Finally, our research provides insights, strategies, and future directions for industry practitioners and marketers.

Molecular Chinese Medicine (MCM) is a recent method of manufacturing and dosing prescriptions that brings several advantages when compared with Traditional Chinese Medicine (TCM). For instance, MCM is highly dissoluble, tastes better than the usual decoction, and the active principles are easily absorbed. Also, the manufacturing process is subject to better quality control. In spite of these benefits, consumers' intentions remain unclear due to the novelty of this technique. Therefore, an assessment of individuals' perceptions is relevant since molecular medicine is redefining how scientists understand and treat diseases, and it can be considered a medical innovation. To fill the research gap, the Value-based Acceptance Model (VAM) (Kim et al., 2007) is used to assess the individuals' perceptions of value and intention to accept MCM. Data from a sample of Macau residents are analyzed by means of structural equation modeling (SmartPLS). The results support the use of the model in our context, thus extending the applicability of the VAM to other settings. Except for 'technicality', the constructs of 'usefulness', 'enjoyment', and 'perceived fee' had a significant impact on the overall 'perceived value' of MCM, and in turn on the behavioral intention to use the innovation. To facilitate the diffusion of this dosage method in the marketplace, it is suggested that communications strategies consider the proposed sources of value when promoting MCM. To further explain the adoption process, it is recommended to include additional factors that may affect consumers' intention to adopt the innovation and extend the analysis to the actual usage.

The decision to accept and use technology innovations has long been a source of debate across disciplines due to the complexity involved in predicting behavior. Recognizing that the subject is vast and fragmented, this paper examines the mainstream technology works to assist researchers to understand, conceptualize and select the most appropriate theoretical framework for their study. Starting with the pioneering effort on Diffusion of Innovations (DOI/IDT), the analysis considers the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM/TAM-2/TAM-3), the Value-based Acceptance Model (VAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT/UTAUT-2) among the most important. A review of the key literature is vital to assessing and identifying research trends, as well as contributing to the discussion of emerging technologies such as Artificial Intelligence (AI), Augmented Reality (AR), Blockchain, Cloud Computing, Internet of Things (IoT), Mobile Apps, etc. Suggestions for future research paths are also provided.

Macau has long been considered to be an example of remarkable economic growth. With the opening of the gaming sector in 2002, the casino and hospitality sector flourished, creating employment opportunities but also imposing several challenges on managers. Since Macau endeavors to be positioned as the center for international business with Portuguese-speaking countries and a platform for trading with China’s Greater Bay Area (GBA), it becomes essential for international enterprises to understand the local dynamics. In light of the limited research available, this study aims to identify management challenges from the perspectives of senior executives in different industries based in Macau. Our findings point out that managers must contend with several issues, such as the lack of a skilled local talent pool, high turnover rates, employees' work attitudes, and a tightly controlled immigration policy. It is also imperative for international managers to nurture relationships and pay attention to the local culture. Our results suggest that Macau has to develop a highly skilled local workforce to attract international companies, while local organizations also have to create an attractive working environment to compete in the marketplace.

Artists are increasingly using blockchain as a tool for trading digital artwork as non-fungible tokens (NFTs); however, some are also beginning to experiment with the blockchain as a medium for generative art, using it as a seed for a generative process or to continuously modify an evolving piece. This paper surveys, reviews, and classifies the state-of-the-art in blockchain-interactive NFTs and presents a liberal-arts critique of the opportunities and threats posed by this technology, whilst addressing existing criticism on the broader topic of art-related NFTs. The paper examines some of the most experimental pieces minted on the Hic et Nunc (HEN) and Teia NFT marketplaces, for which a purpose-built research tool was developed. The survey reveals some reliance on centralised infrastructure, namely blockchain indexers, placing undesired trust on third parties which undermines the potential longevity of the artwork. The paper concludes with recommendations for artists and NFT platform designers for developing more resilient and economically sustainable architectures.