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<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>

Online shopping in Macau has developed rapidly in recent years. And the success of Taobao is significantly hard to not notice. Its’ sales are breaking the record every year. However, there are a lot of negative comments towards Taobao. Various researches and data have shown that live-streaming is one of the biggest contributions towards Taobao’s sales and record breaking. This research aims to investigate deeply to understand how Taobao counters those issues and the role of live-streaming in relation to it. Based on a review of the literature in the relevant areas , qualitative methodology is adopted after thorough considerations. A small sample size of 10 were selected to conduct semi-structured in-depth interviews and the participants agreed to respond to answer the original interview questions and the follow-up questions. Analysis of the responses demonstrated e-customer service is the most influential variable towards repurchase intention. Live-streaming strategy can effectively and directly reduce constomer’s uncertainty of products and increase the efficiency of responsiveness. And product uncertainty and responsiveness speed are variables that impact purchase intention. The result demonstrated live-streaming's effectiveness in combating multiple negative aspects of Taobao and strengthening the positive aspects. On this basis, live-streaming is an impactful method to combat Taobao. In addition, e-service in terms of sufficiency of the staff’s communication skill have been found important towards customer’s satisfaction. A gap related to such an issue has been recommended in the further research recommendations along with other factors or sample groups, which are needed to explore deeply in the future

School-age children and adolescents face several psychological conditions frequently associated with negative consequences on behavioral and mental problems. Their level of mental resilience may affect their responses to academic or interpersonal issues and coping with challenges, which in turn affects their mental health. This study aims to characterize the current status of the psychopathology and resilience of secondary students and to analyze the relationship between psychopathology and resilience in a sample of 80 girls aged 12–18 was selected by cluster sampling from one private secondary school with six grades in Macao. In this study, we used the Achenbach System of Empirically Based Assessment (ASEBA) to assess behavioral and emotional problems and the Resilience Scale for Chinese Adolescents to assess resilience. A total of 78 valid questionnaires were obtained for CBCL, 78 for TRF, 80 for YSR, and 77 for Resilience Scale and data were analyzed by using SPSS. The results reveal that clinical prevalence of Total Problems (YSR, 27.5% > CBCL, 19.2% > TRF, 15.4%) and Internalizing Problems (YSR, 22.5% > CBCL, 17.9% > TRF, 11.5%) from the perspective of adolescents was higher than that from the perspectives of parents and teachers. Senior students exhibited higher frequency on the borderline clinical range than Junior students. (χ2(2, N=80) =14.56, p<.001). The average score of resilience is 3.24±0.51, which is above the middle level. Regarding the YSR scale and Resilience scale, we found that the score of Affect Control is significantly negatively correlated with the score of Internalizing Problems (r = -.354, p<.01). Family Support is also significantly negatively correlated with the score of Internalizing Problems (r = -.302, p<.01). Good affect control and family support can reduce various emotional and behavioral problems. The results of the study found the resilience level can negatively affect internalizing problem behaviors and externalizing problem behaviors. The results are promising and can give clues for preventing and promoting measures regarding mental health issues to both family and school education contexts, as creating a sustainable development strategy of improving adolescents’ mental resilience quality

Technology is an essential and valuable tool nowadays. New technology and innovations are introduced to the public day by day. Metaverse will be a new trend, as the Macau government has been trying to promote this technology since the COVID-19 pandemic is still here. Before this technology goes deeply to the public, this paper attempts to examine the consumer’s perspective of Metaverse and understand the cognition of Macau people about Metaverse. And bring out what factors and conditions will make them accept this technology. A qualitative research method will address the questions and problem to understand consumer perspectives towards this technology. Entrepreneurs, managers, and professionals will be invited to take part in this research. Ten interviews will be carried out in this research for data analysis, which may provide a board overview of this technology in Macau and give recommendations to local entrepreneurs. In conclusion, consumers think it is still not a well-developed technology and is not globally used at this stage. In contrast, if this technology is ready-to-use, it will be a helpful assistant in their businesses. They expect the metaverse to be fully developed in ten or more years

The insurance companies in Macau are potentially facing a crisis of high turnover rates, exacerbated by the limited studies conducted on the insurance industry to address this issue, as the gaming and travel industries are currently experiencing a significant demand for human resources due to economic recovery. In light of this, a study was conducted to better understand the attitudes of 105 currently employed insurance agents in Macau insurance companies, specifically their commitment and thoughts of staying or leaving their employers. The study examined several independent variables (distributive justice, perceived organizational support (POS), job satisfaction, and caring climate) in relation to insurance agents’ turnover intention and the role of affective commitment. The aim was to determine the association between these variables and turnover intentions among insurance agents. The snowballing methodology was employed to effectively engage with the insurance agents and gain insights into their perspectives. The results of the statistical analysis revealed positive correlations between all independent variables and affective commitment. Job satisfaction and POS were identified as strong positive predictors. Additionally, mediated regression analyses demonstrated that affective commitment significantly mediated the relationship between all independent variables and turnover intention. Finally, the study provides implications for insurance company management to address and reduce the high turnover rate. Furthermore, the importance of future orientation is further discussed

"Over time, the large shopping malls in Macao will require some changes to improve space utilization, resulting in renovation projects that affect indoor particulate matter (PM10 and PM2.5) concentrations. Employees work long hours in an environment where the ambient air quality is poor, directly affecting their work efficiency. Nonetheless, the concentration of PM produced by the interior renovation of shopping malls has yet to receive particular attention. Therefore, this study will investigate IAQ, in particular, PM10 and PM2.5 in large-scale shopping mall renovation projects in three different indoor locations (i.e., public, renovation, and construction areas) to understand the causes of indoor PM10 and PM2.5. This study will collect on-site PM data for analysis, examine whether the current control measures are appropriate and propose some improvements. The data collected will be compared with IAQ standards from the World Health Organization (WHO) and the Macao Meteorological and Geophysical Bureau (SMG), specifically PM concentrations. The research results can provide a reference guide for decision-makers, management, construction teams, design consultant teams and renovation teams of large-scale projects. In addition, the monitoring of IAQ can ensure a comfortable environment for employees and customers."

This study aims to investigate gender-differentiated parenting and the factors that affect parent-adolescent relationships in Macao families. The study will address the following research questions: A) Does gender-differentiated parenting exist in Macao families? B) How does the academic level of parents relate to conflict resolution and acceptance levels? C) How does the length of time parents have lived together relate to conflict resolution and acceptance levels? D) How does the sibling position of adolescents relate to conflict resolution and acceptance levels? The study employed a quantitative research approach with a purposive and convenient sample of parents with children aged between 12 to 18 years old in Macao. The data were collected using the Parent-Child Interaction Questionnaire—Revised-Parent version (PACHIQ-R-P) through a questionnaire survey from May to August 2022. Out of the 172 completed questionnaires, seven were invalid, resulting in 165 valid questionnaires. The findings showed that gender differentiation in parenting was confirmed, with significant results showing that fathers had lower acceptance and conflict resolution levels when their child was a boy. Mothers showed similar acceptance and conflict resolution levels regardless of their child's gender. Furthermore, the study found that parents' acceptance of their children was influenced by their academic level, length of time living together, and the child's sibling position. This study is the first of its kind in Macao and could provide valuable insights for family and adolescent services in the region

Due to the expansion of the Internet and advancements in technology, e-commerce has been frequently and widely used nowadays. The popularity of online shopping continues to develop and become increasingly common, yet, the concept of impulsive buying has consistently drawn significant attention over the years. In order to fit into the current shopping trend, recognizing the needs and wants of online shoppers as well as providing appropriate approaches are essential tasks for companies to achieve. The question of how to attract consumers to make purchases has been a concern for a long time, and in fact, it is necessary to explore consumers’ online purchase decisions in relation to their impulse buying behavior. In accordance with current academic knowledge, the main objective of this study is to investigate factors that influence consumers' online impulsive buying behavior based on external stimuli (such as sales promotions and websites characteristics) and the elements of marketing mix strategy (product, price, place, and promotion). According to the analysis, the promotion strategy has been identified as the most significant influence on consumers’ decision to make an online impulsive purchase. Therefore, the findings from this study are beneficial for companies and marketers to build a framework in order to develop suitable and effective strategies in order to encourage and stimulate consumers' desire for purchases. Furthermore, the research applies the qualitative methodology by conducting semi-structured interviews with 11 consumers who have previously experienced an online impulse buying

Macao is a city of culture, and history and culture are the wealth of Macao. Over the centuries, the exchange and transmutation of Chinese and Western cultures have given Macao a unique cultural charm, and have also formed and preserved a considerable amount of cultural heritage. Cultural heritage has received increasing attention from all sectors of the community in the tourism industry in Macao, the promotion of the preservation and transmission of cultural heritage through tourism development has become a new issue in the tourism sector. As an independent art form in the urban public space, tile painting has both practical and aesthetic functions, and is a special vehicle for the convergence of multiple cultures in the urban cultural ecology. It is also a medium through which the city's cultural message can be fully disseminated. The paper presents a detailed analysis of the strengths, weaknesses, opportunities and challenges of the development of Macao's cultural heritage tile murals, based on an introduction to the existing status of Macao's cultural heritage tile murals, using the SWOT analysis method, which provides a reference for Macao's cultural heritage tourism

This thesis mainly discusses and compares the human rights situation and the problems in China, the USA and the UK. Also, the thesis will give the solution of how to make the world's human rights situation more fairly. Because we sometimes listen to these countries use cruel ways to suppress the opponents from the news. So I think this will be very suitable for understanding the current human rights situation, problems and movements in these countries. This thesis mainly uses the secondary data analysis method to collect and analyse the data. After analysing the data, three main issues affecting human rights were identified. These issues are race, religion, and network privacy. Other important factors still influence human rights, but this dissertation focused on the three issues identified. Finally, I will give two to three recommendations to practice human rights more fairly. Although the step will be very small, we can greatly improve the fair human rights in the future

With the rapid urban development, Macao SAR has become one of regions with the with highest population density in the world, characterized by high traffic flow and dense building aggregations. Noise has become one of the major environmental problems in Macao. Besides having an impact on human health and wellbeing, noise pollution is known to impact ecological systems and the image of a place. Before proposing a plan to reduce noise pollution, it is necessary to have a general understanding of the current noise levels in Macao, how they have changed over time and the main noise pollution sources and environmental concerns. This dissertation relies on the publicly available data from DSPA (Macao Environmental Protection Bureau) monitoring stations concerning noise levels over the past decade. The main research goals were: 1) Characterize changes in noise levels from 2010 to 2021 during daytime, nighttime, and full-day from multiple noise stations located in Macao, Taipa, and Coloane Peninsula; and 2) associate changes in noise levels with potential factors such as location, number of residents/tourists, number of vehicles, among others. This work provides an important framework for future studies concerning noise monitoring and mitigation strategies

The purpose of the study was to explore the smoking behaviour of the smokers living in Macao. I was part of the 1st group of doctors to have chosen to initiate smoking cessation in Macau. In addition to my diverse academic background of study in laws- a dissertation about the effect of tobacco control program in Macao (submitted in 2011), a master in Public Administration, and five years of working experiences as an Inspector Assistant of tobacco, I had the conviction that I have to write to share my experience and knowledge about smoking cessation to contribute to the field of counselling and psychotherapy as there is little research data concerning smoking prevalence and demographics in Macao. This study consists of two parts – PART I presents the quantitative data collected by a questionnaire-survey over 1378 smokers and PART II qualitative data from semi-structured interviews with 10 adult smokers to explore their experiences of smoking and smoking cessation in Macao. Quantitative data analysis was conducted with the SPSS, while qualitative analysis with coding and theme identification by following the grounded theory procedures. The study found that about 85% smoker surveyed consumed more than half a pack of cigarette per day and about 31% reported various symptoms like irritability, fatigue, loss of appetite and difficulties in concentration. The qualitative study has identified major positive factors related to initiation and maintenance of smoking cessation, namely health concerns, financial concerns and family support. Major negative factors related to relapse of smoking are peer influences, smoking of family members, and impacts of stressful life events. Based on findings of the study, it is argued that preventive anti-smoking education should be implemented among young people. Promotion of health education and preventive anti-smoking strategist and policy in Macao are discussed. The data collected indicate the fact that individuals who have pathologies of the cardiovascular system as a motivating factor for contemplating or taking actions for smoking cessation. Moreover, financial problems, gender (male predominantly), married with family support, higher educational level, without psychological diseases, better economic status, lower nicotine dependent are predictors to success in quit smoking. It also raises the possible need to deepen some evaluation parameters hither to be only superficially addressed. Therefore, and by limitations inherent to the study, this hypothesis needs further investigation. I argue that non-pharmacological treatment methods alone have proven to be effective in the smoking cessation process. However, it is argued that this combined with pharmacological therapy, in particular in specialized consultations, would be more effective and capable in increasing success rates in smoking cessation

The gold standard to detect SARS-CoV-2 infection considers testing methods based on Polymerase Chain Reaction (PCR). Still, the time necessary to confirm patient infection can be lengthy, and the process is expensive. In parallel, X-Ray and CT scans play an important role in the diagnosis and treatment processes. Hence, a trusted automated technique for identifying and quantifying the infected lung regions would be advantageous. Chest X-rays are two-dimensional images of the patient’s chest and provide lung morphological information and other characteristics, like ground-glass opacities (GGO), horizontal linear opacities, or consolidations, which are typical characteristics of pneumonia caused by COVID-19. This chapter presents an AI-based system using multiple Transfer Learning models for COVID-19 classification using Chest X-Rays. In our experimental design, all the classifiers demonstrated satisfactory accuracy, precision, recall, and specificity performance. On the one hand, the Mobilenet architecture outperformed the other CNNs, achieving excellent results for the evaluated metrics. On the other hand, Squeezenet presented a regular result in terms of recall. In medical diagnosis, false negatives can be particularly harmful because a false negative can lead to patients being incorrectly diagnosed as healthy. These results suggest that our Deep Learning classifiers can accurately classify X-ray exams as normal or indicative of COVID-19 with high confidence.

The gold standard to detect SARS-CoV-2 infection consider testing methods based on Polymerase Chain Reaction (PCR). Still, the time necessary to confirm patient infection can be lengthy, and the process is expensive. On the other hand, X-Ray and CT scans play a vital role in the auxiliary diagnosis process. Hence, a trusted automated technique for identifying and quantifying the infected lung regions would be advantageous. Chest X-rays are two-dimensional images of the patient’s chest and provide lung morphological information and other characteristics, like ground-glass opacities (GGO), horizontal linear opacities, or consolidations, which are characteristics of pneumonia caused by COVID-19. But before the computerized diagnostic support system can classify a medical image, a segmentation task should usually be performed to identify relevant areas to be analyzed and reduce the risk of noise and misinterpretation caused by other structures eventually present in the images. This chapter presents an AI-based system for lung segmentation in X-ray images using a U-net CNN model. The system’s performance was evaluated using metrics such as cross-entropy, dice coefficient, and Mean IoU on unseen data. Our study divided the data into training and evaluation sets using an 80/20 train-test split method. The training set was used to train the model, and the evaluation test set was used to evaluate the performance of the trained model. The results of the evaluation showed that the model achieved a Dice Similarity Coefficient (DSC) of 95%, Cross entropy of 97%, and Mean IoU of 86%.

The Covid-19 pandemic evidenced the need Computer Aided Diagnostic Systems to analyze medical images, such as CT and MRI scans and X-rays, to assist specialists in disease diagnosis. CAD systems have been shown to be effective at detecting COVID-19 in chest X-ray and CT images, with some studies reporting high levels of accuracy and sensitivity. Moreover, it can also detect some diseases in patients who may not have symptoms, preventing the spread of the virus. There are some types of CAD systems, such as Machine and Deep Learning-based and Transfer learning-based. This chapter proposes a pipeline for feature extraction and classification of Covid-19 in X-ray images using transfer learning for feature extraction with VGG-16 CNN and machine learning classifiers. Five classifiers were evaluated: Accuracy, Specificity, Sensitivity, Geometric mean, and Area under the curve. The SVM Classifier presented the best performance metrics for Covid-19 classification, achieving 90% accuracy, 97.5% of Specificity, 82.5% of Sensitivity, 89.6% of Geometric mean, and 90% for the AUC metric. On the other hand, the Nearest Centroid (NC) classifier presented poor sensitivity and geometric mean results, achieving 33.9% and 54.07%, respectively.