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The COVID-19 pandemic has posed a significant public health challenge on a global scale. It is imperative that we continue to undertake research in order to identify early markers of disease progression, enhance patient care through prompt diagnosis, identification of high-risk patients, early prevention, and efficient allocation of medical resources. In this particular study, we obtained 100 5-min electrocardiograms (ECGs) from 50 COVID-19 volunteers in two different positions, namely upright and supine, who were categorized as either moderately or critically ill. We used classification algorithms to analyze heart rate variability (HRV) metrics derived from the ECGs of the volunteers with the goal of predicting the severity of illness. Our study choose a configuration pro SVC that achieved 76% of accuracy, and 0.84 on F1 Score in predicting the severity of Covid-19 based on HRV metrics.

Information contained within documents is an essential ingredient of any office operation. A content management application (CMA) is an organization plan for the conception, use, retention, disposal and selective preservation of its data. Using an appropriate CMA framework can greatly help Macao Government agencies, for instance, that are increasingly using electronic means to create, exchange and store a major variety of records daily. By definition, a record is information, in whatever form, for government functions, activities, decisions and other important transactions. As expected, as the volume of electronic information increases, so does the complexity of managing electronic records. This project goal was to evaluate the software capabilities of the Alfresco© Enterprise Content Management (ECM) against a set of functional requirements, aimed by the Macao Government agency. Drawing on the results of this evaluation, the present analysis concludes that Alfresco© ECM is capable of supporting an entire agency needs related to the management of its records content.

Family business are the dominant form of business in the world, and Chinese family business (CFB) is a unique type of family business that relies on collective action to survive. This paper argues that in CFBs, entrepreneurial actions are transgenerational collective endeavors, and successors are groomed as stewards of the family legacy. Work-life relationship in CFBs is about synergy and not balance because the family identity is the business identity, and vice-versa. Using five in-depth case studies, this research introduces an alternative understanding of CFBs and proposes a model of work-life synergy in transgenerational entrepreneurship based on discussion of five theory-based propositions. This model explains that through emphasizing on the business family's shared value and entrepreneurial legacy, elements of trust, shared identity and stewardship of family members are enhanced which leads to collective action and goal of the business family, resulting in transgenerational entrepreneurship. Limitations and future research are presented.

In recent years, entrepreneurship and innovation have been highly propagandised for Macau's economic development, diversification, and the Greater Bay Area (GBA). Since 2013, efforts have been exerted by the Macau government to encourage and support entrepreneurship, from the launching of the Young Entrepreneurs' Aid Scheme in 2013 and the Macau Young Entrepreneur Incubation Centre in 2015. While the failure rate of startups has been considered high in most parts of the world, the rate was only as low as 14% in Macau, with many businesses created every year. This research aims to study the unique entrepreneurial environment for small-to-medium enterprises (SMEs) starting up in Macau from the experience of local entrepreneurs who are benefactors of government support. In-depth interviews were conducted to understand the experience and perceptions of these entrepreneurs as they go through each stage of the entrepreneurial process. Existing research on entrepreneurial processes varies from the two-stage process, which focuses on the beginning of an enterprise, to the different models of various stages from ideas generation to exit or long-term development. From the consolidation of the literature on the entrepreneurial process, five key stages were taken to guide this qualitative research. Findings suggested that idea validation at the start of the entrepreneurial process is almost non-existent amongst our research subjects. Yet it does not affect the implementation and growth of these SMEs. The growth strategies tend to be steady and for the long term, with most SMEs having no consideration of an exit plan.

This research explores innovation of traditional SMEs that do not actively invest in innovation. Elements of open innovation have been identified in these firms in their effort to build social capital which they perceive as pertinent to their businesses. The result of the research shows that instead of using social capital as means for innovation, the unintentional practice of open innovation has contributed to the development of social capital, which further opens up potential for globalization. As a result, a model of open innovation as means of developing social capital for enhancing globalization potential for SMEs was developed.

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

This paper presents an algorithm that applies metrics derived from automatic QRS detection and segmentation in electrocardiogram signals for analyzing Heart Rate Variability to study the evolution of metrics in the frequency domain of a clinical procedure. The analysis was performed on three sets of elderly people, who are categorized according to frailty phenotype. The first set was comprised of frail elderly, the second pre-frail elderly, and the third robust elderly. Investigators from many disciplines have been encouraged to contribute to the understanding of molecular and physiological changes in multiple systems that may increase the vulnerability of frail elderly. In this work, the frailty phenotype can be characterized by unintentional weight loss, as self-reported, fatigue assessed by self-report, grip strength (measured directly), physical activity level assessed by self-report and gait speed (measured). The results obtained demonstrate the existence of significant differences between Heart Rate Variability metrics for the three groups, especially considering a higher preponderance for sympathetic nervous system for the group of robust patients in response to postural maneuver.

It is argued that the role of the Chinese government to support the cross-border operations of Chinese firms is to assist these firms in overcoming their limited established brands, and their disadvantages in technology and managerial resources, which were also the reasons why such firms decided to enter emerging markets instead of developed markets. This strategic choice is preferred to avoid direct confrontation with established firms from developed countries endowed with superior ownership advantages. Therefore, Chinese resources seeking firms innovate by increasing investment in developing and emerging markets to develop unique ownership advantages for sustainable market development and competitive advantage. This research investigates the ownership advantages of resources seeking Chinese firms in these markets using the OLI theory. The paper contributes to explaining the specific advantages of Chinese MNEs when entering emerging markets. The study applied a two-stage qualitative methodology to examine Chinese firms operating in Nigeria. The first stage included an exploratory study based on interviews with key informants and experts while the second stage included a case study methodology. The study focused on resources seeking Chinese MNEs operating in Nigeria.

In 2000, the China-Africa relationship was further strengthened with the establishment of the Forum on China-Africa Cooperation (FOCAC). The FOCAC offers a platform for consultation and cooperation mechanisms aimed at deepening diplomatic, security, trade and investment relations between China and African countries. Later came the Belt and Road Initiative (BRI) in 2013, an international trade network initiated by China that connects the three continents of Asia, Europe and Africa. The BRI focuses on the following key areas: cultural exchange; policy coordination; facilities connectivity; trade and investment; and financial integration. The BRI shares development objectives similar to those of the United Nations’ Sustainable Development Goals (SDGs). In fact, the BRI implements part of the SDGs and provides a practical mechanism to strengthen the Sino-Africa relationship, which Africa can leverage to meet its Sustainable Goals. Africa is linked through the “Road” of the BRI plan and has received infrastructural projects funded by China to facilitate trade and integration of the national economies along the trading route. Through the establishment of Economic and Trade Zones which attracts investments from Chinese companies, and building infrastructures such as sea ports and railways, China through the BRI framework is helping Africa meet UN SGD Goal 9 concerning industry, innovation and infrastructure. A practical effect is that the BRI is helping African countries overcome the infrastructure gap, create jobs, acquire skills and promote integration between countries.

Background and objective Intrauterine Growth Restriction (IUGR) is a condition in which a fetus does not grow to the expected weight during pregnancy. There are several well documented causes in the literature for this issue, such as maternal disorder, and genetic influences. Nevertheless, besides the risk during pregnancy and labour periods, in a long term perspective, the impact of IUGR condition during the child development is an area of research itself. The main objective of this work is to propose a machine learning solution to identify the most significant features of importance based on physiological, clinical or socioeconomic factors correlated with previous IUGR condition after 10 years of birth. Methods In this work, 41 IUGR (18 male) and 34 Non-IUGR (22 male) children were followed up 9 years after the birth, in average (9.1786 ± 0.6784 years old). A group of machine learning algorithms is proposed to classify children previously identified as born under IUGR condition based on 24-hours monitoring of ECG (Holter) and blood pressure (ABPM), and other clinical and socioeconomic attributes. In additional, an algorithm of relevance determination based on the classifier is also proposed, to determine the level of importance of the considered features. Results The proposed classification solution achieved accuracy up to 94.73%, and better performance than seven state-of-the-art machine learning algorithms. Also, relevant latent factors related to HRV and BP monitoring are proposed, such as: day-time heart rate (day-time HR), day-night systolic blood pressure (day-night SBP), 24-hour standard deviation (SD) of SBP, dropped, morning cortisol creatinine, 24-hour mean of SDs of all NN intervals for each 5 minutes segment (24-hour SDNNi), among others. Conclusion With outstanding accuracy of our proposed solutions, the classification system and the indication of relevant attributes may support medical teams on the clinical monitoring of IUGR children during their childhood development.

Neuromarketing lies at the intersection of three main disciplines: psychology, neuroscience, and marketing, and it has been a successful neuroscientific approach for the study of real-life choices such as consumer behavior [1]. A current gap in the cosmetics field is the lack of published research studies, considering the marketing investment done yearly in this category. With the rapid economic expansion and the rise of social media in China, consumers' interest in beauty is growing. Even though the Chinese cosmetics sector is rapidly expanding, no studies have been done with Chinese consumers. This study aims to employ the same approach as previously done in consumer neuroscience studies to evaluate cosmetic brands' marketing strategy to understand better if immediate emotional responses can be measured using Electrodermal Activity (EDA). Here, we focus on cosmetics products advertisement as a model to understand consumer preference formation and choice. Eighteen Chinese female consumers were recruited between 19 and 37 years old. From the results obtained, it was understood that none of the participants have voted for the product advertisement for which they showed higher emotional arousal. However, it appears that the participants' preference is for the products for which the brand awareness is stronger since the product advertisements with more votes are the ones for the Korean brand used. The product advertisements with Asian faces were the ones with more votes, suggesting that Asian faces have engaged consumer preference. However, the product advertisements for the Brazilian brands, unknown to the Chinese public, were the ones with fewer votes, although, those product advertisements were the ones with more emotional arousal per minute. Those advertisements were also those with non-Asian faces, suggesting that this feature influenced voting decisions. From this study, it has been observed that Electrodermal Activity is a measure of emotional arousal that by itself cannot be translated into consumer engagement. Therefore, it is also proposed to evaluate brand awareness in future studies related to product advertisements. The physical features of the people included in the advertisements is also suggested to be further evaluated in future studies since a different cultural background seems to influence the consumers' engagement. Furthermore, using EDA to complement other neurophysiological tools like facial expression analysis is also suggested for future studies to have evidence about the nature of the emotions raised.

The knowledge of spatial distribution of grasshoppers can be very relevant for agricultural planning purposes. On the other hand, the comparison of spatial interpolators for efficiency and reliability reasons is also a key factor to understand interpolation maps outcomes (versus reality). At last, but not least, the use of open Web geographical tools to disseminate true spatial inferential methods to address spatial issues is still quite limited (if none) in high schools and universities, particularly in Geography subjects. If the latter can be addressed with myGeoffice©, the first issue will use the Utah, USA, dataset (58 samples) to layout the spatial distribution of grasshoppers and understand the counties that are more pro to this kind of agriculture infestation. Inverse Distance Weighted (IDW), Moving Average (MA), Multi-quadratic, Inverse Multi-quadratic and Nearest Neighbor (NN) will produce interpolated surfaces of grasshopper’s properties. Efficiency of spatial interpolators was assessed in this writing based on the prediction error’s statistics derived from the difference between the estimation and the real samples on a cross-validation procedure. Remarkably, results show that NN was the most accurate one when compared with the remaining deterministic approaches at sample’s locations.

For a long time, Geography did not hold a specific mathematical approach for any interpretation of space and this was the key reason why Geography degrees covered a wide variety of subjects such as demography, geology or topography to fulfill its curriculum. Yet from the 90’s, Geography finally created its own research agenda to meet four vital questions of any true geographer: “Where is …?”, “Is there a general spatial pattern?”, “What are the anomalies?” and “Why do these phenomena pursue certain spatial distribution?” The present review article addresses ten different spatial (point, regression and event) issues for learning and teaching aim where statistics play a major background role on the outcomes of myGeoffice© free Web GIS platform. These include cluster analysis, geographically weighted regression (GWR), ordinary least squares (OLS) regression, path analysis, minimum spanning tree, linear regression, space-time clustering and point patterns, for instance. Although the technical viewpoint of the algorithms is not explained at fully, this review paper makes a rather strong emphasis on the result’s interpretation, their respective meaning and when these techniques should be applied in a learning/teaching context.

This paper starts to address the affect and side-effects of social media on people’s live in a pure contemplation perspective. Social networks are revised and some issues regarding its impact on education was not forgotten such as the teacher role in the digital classroom, formal versus informal learning or Web 2.0 tools use. Since Moodle is the first Learning Management System whilst Facebook is the first social network in the world, a survey was accomplished with two independent classes of e-business students at University of Saint Joseph, Macao, China, on their attitudes toward both online services in a learning framework. In general, the results confirms to a certain extent others previous studies on the question of whether using Facebook as an educational tool is more effective than Moodle.

One of the purposes of this study is to evaluate how the choice of teaching method can be assisted by knowledge of a student’s personality type and learning style. The present research is undertaken in the context of Web 2.0 tools use within the Portuguese literature subject at Escola Portuguesa de Macao (EPM). The Felder-Soloman index of learning style (ILS) and the Myers-Briggs Type Indicator (MBTI) based upon Jung’s theory of psychological nature were used as measures of learning style and personality type with 8th grade EPM students. Descriptive and chi-squared correlation statistical results of the associations between personality and learners types are presented. These results are discussed positing that the knowledge of student’s personality traits and learning styles together may have a notable implication for teaching methods.

Even with more than 12 billion vaccine doses administered globally, the Covid-19 pandemic has caused several global economic, social, environmental, and healthcare impacts. Computer Aided Diagnostic (CAD) systems can serve as a complementary method to aid doctors in identifying regions of interest in images and help detect diseases. In addition, these systems can help doctors analyze the status of the disease and check for their progress or regression. To analyze the viability of using CNNs for differentiating Covid-19 CT positive images from Covid-19 CT negative images, we used a dataset collected by Union Hospital (HUST-UH) and Liyuan Hospital (HUST-LH) and made available at the Kaggle platform. The main objective of this chapter is to present results from applying two state-of-the-art CNNs on a Covid-19 CT Scan images database to evaluate the possibility of differentiating images with imaging features associated with Covid-19 pneumonia from images with imaging features irrelevant to Covid-19 pneumonia. Two pre-trained neural networks, ResNet50 and MobileNet, were fine-tuned for the datasets under analysis. Both CNNs obtained promising results, with the ResNet50 network achieving a Precision of 0.97, a Recall of 0.96, an F1-score of 0.96, and 39 false negatives. The MobileNet classifier obtained a Precision of 0.94, a Recall of 0.94, an F1-score of 0.94, and a total of 20 false negatives.