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Full bibliography 2,190 resources
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Macau, Macau Business, MAG, MB, MB Featured, Opinion | Macau’s development of international and tertiary sector industries is the watchword for its long-overdue diversification. Is Macau ready for this?
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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.
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" Air pollution in Macau has become a serious problem following the Pearl River Delta’s (PRD) rapid industrialization that began in the 1990s. While there has been continual improvement in recent years, harmful air pollutant concentration levels are still common, impacting Macau residents' health and creating long-term medical costs to local society. With this in mind, Macau needs an air quality forecast system that accurately predicts pollutant concentration and an early alert system instead of only daily real-time reminders. Some scholars have previously carried out studies to develop an air quality forecast for Macau by successfully using statistical models. Therefore, pursuant to the outcomes of previous studies, this dissertation aims to build upon research results and explore further possibilities of building a better ML air quality forecast model based on the time series of air pollutants concentration and meteorological data. Four different state-of-the-art ML algorithms were used to create predictive models to forecast PM2.5, PM10, and carbon monoxide (CO) concentrations for the next 24 and 48-hour. These were Support Vector Machine (SVM), Artificial Neural Networks (ANN), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). In addition, Multiple Linear Regression MLR, a standard ML model, was used for this dissertation as a baseline reference for performance comparison. The daily measurements of air quality data in Macau from 2016 to 2021 were collected for this dissertation. The 2020 and 2021 datasets were used for model testing while the four-year data prior to 2020 and 2021 were used to build and train the ML models. The results showed that SVM, ANN, RF, and XGBoost were able to provide a very good performance in building up a 24-hour forecast with higher R2 and lower RMSE, MAE, and BIAS. Meanwhile, all ML models in 48-hour forecasting performance were satisfactory enough to be accepted as a two-day continuous forecast even if the R2 value was lower than the 24-hour forecast. The 48-hour forecasting model could be further improved by proper feature selection based on the 24-hour dataset, using the SHAP value test, and the adjusted R2 value of the 48-hour forecasting model."
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Informal recycling plays a crucial role in municiapl solid waste management in many cities, particularly in the global South. This study examines the practices, challenges, and opportunities of informal recycling in Macau, a small city and Self Autonomous Region (S.A.R.) in China. Using qualitative research methods, including semi-structured interviews, this study explores the motivations and strategies of informal recyclers, the challenges they face, and the potential for collaboration with formal waste management systems. The findings of this study reveal that informal recycling in Macau is a complex and multifaceted reality and practice that involves a range of actors, from waste pickers to small-scale processors to exporters, all with their specific challenges. Informal recyclers are motivated by economic necessity, and they employ a variety of strategies to collect and process recyclable materials. However, they also face significant challenges, including high rental and transportation costs, lack of manpower, China’s waste import policies and ensuing restrictions, fluctuating global price rates of materials and the unstable income as serious consequence, accompanied by limited support from the local Government. This study also identifies opportunities for sustainable development of informal recycling in Macau, supported by the analysis of data collected via questionnaire survey regarding Macau citizens’ waste separation habits and their willingness to pay for resource separation and recovering process. The identified oppurtunities include establishing partnerships between informal and formal waste management actors, improving the infrastructure, and introducing environmental levy system and consistent policies and regulations. Overall, this study contributes to a better understanding of the role of informal recycling sector in waste management in Macau and provides insights into potential strategies for improving the sustainability of resource and waste management practices in the city
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Virtual reality, a computer-generated 3D environment, allows one to navigate and possibly interact, resulting in real-time simulation of one or more of the user’s five senses (Gutierrez et al., 2008; Vince, 2004). Virtual tours and places have swiftly become popular in education, professional training, arts, exhibitions, and medication and rehabilitation. The empirical studies derived from the PhD thesis research aim to identify the conditions for Macao’s single-user experience to achieve mindfulness in virtual reality through immersion and interactivity.
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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.
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The continuous development of robust machine learning algorithms in recent years has helped to improve the solutions of many studies in many fields of medicine, rapid diagnosis and detection of high-risk patients with poor prognosis as the coronavirus disease 2019 (COVID-19) spreads globally, and also early prevention of patients and optimization of medical resources. Here, we propose a fully automated machine learning system to classify the severity of COVID-19 from electrocardiogram (ECG) signals. We retrospectively collected 100 5-minute ECGs from 50 patients in two different positions, upright and supine. We processed the surface ECG to obtain QRS complexes and HRV indices for RR series, including a total of 43 features. We compared 19 machine learning classification algorithms that yielded different approaches explained in a methodology session.
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In 2020, the World Health Organization declared the Coronavirus Disease 19 a global pandemic. While detecting COVID-19 is essential in controlling the disease, prognosis prediction is crucial in reducing disease complications and patient mortality. For that, standard protocols consider adopting medical imaging tools to analyze cases of pneumonia and complications. Nevertheless, some patients develop different symptoms and/or cannot be moved to a CT-Scan room. In other cases, the devices are not available. The adoption of ambulatory monitoring examinations, such as Electrocardiography (ECG), can be considered a viable tool to address the patient’s cardiovascular condition and to act as a predictor for future disease outcomes. In this investigation, ten non-linear features (Energy, Approximate Entropy, Logarithmic Entropy, Shannon Entropy, Hurst Exponent, Lyapunov Exponent, Higuchi Fractal Dimension, Katz Fractal Dimension, Correlation Dimension and Detrended Fluctuation Analysis) extracted from 2 ECG signals (collected from 2 different patient’s positions). Windows of 1 second segments in 6 ways of windowing signal analysis crops were evaluated employing statistical analysis. Three categories of outcomes are considered for the patient status: Low, Moderate, and Severe, and four combinations for classification scenarios are tested: (Low vs. Moderate, Low vs. Severe, Moderate vs. Severe) and 1 Multi-class comparison (All vs. All)). The results indicate that some statistically significant parameter distributions were found for all comparisons. (Low vs. Moderate—Approximate Entropy p-value = 0.0067 < 0.05, Low vs. Severe—Correlation Dimension p-value = 0.0087 < 0.05, Moderate vs. Severe—Correlation Dimension p-value = 0.0029 < 0.05, All vs. All—Correlation Dimension p-value = 0.0185 < 0.05. The non-linear analysis of the time-frequency representation of the ECG signal can be considered a promising tool for describing and distinguishing the COVID-19 severity activity along its different stages.
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Buddhism was founded by Shakyamuni, and this religion has appeared in opposition to Brahmanism's caste system since its inception. Shakyamuni emphasized the important concept of “all beings are equal” from the very beginning. Buddhism spread from India to other regions, and was introduced to China through Central Asia. In China, Buddhism merged the two native cultures of Confucianism and Taoism and finally produced the socalled Chinese Buddhism. Buddhism and its value of equality were also developed and extended in China, and finally spread to Japan. After Buddhism was spread to Japan, it developed rapidly due to official support. Different Buddhist sects have established their own temples in Japan, and among them, Zen Buddhism has the greatest influence among all social classes in this country. Later, after years of development, Zen Buddhism penetrated into many aspects of Japanese culture, such as religion, aesthetics, garden design, samurai spirit and tea ceremony. With the spread of Zen Buddhism, the core value of Buddhism which is “Buddhist concept of equality” was also spread to Japan. The tea ceremony is precisely the place where this value of equality can be detected. This dissertation explains the many processes that reflect this value no matter inside or outside the tea room, and argues that the spirit of the tea ceremony is to pursue the value of equality
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The demand for plastic has led to enormous plastic waste in the environment, which persist and negatively impact the ecosystems. Polyethylene terephthalate (PET) is one of the most common thermoplastic polymers available on the market. The concerns about plastic waste generated an interest in strategies to enhance its biodegradation and finding alternative polymers. In this work was investigated the possibility of using bacteria to degrade PET and to produce bioplastics (Polyhydroxyalkanoates, PHAs). Finally, the integration of the two processes was tested. Overall, the work aimed to investigate the potential to recycle PET into bioplastic using bacteria. The potential of bacterial consortia from various environmental samples to degrade PET granules in liquid matrix was investigated. . The results revealed maximum PET granules degradation of 1.1 % by one of the tested consortia. PET degradation intermediate terephthalic acid (TPA) was not detected at the end of 55 days. Fourier-transform infrared spectroscopy (FTIR) results showed major spectral peak shifts and bends on PET chemical structure compared to non-inoculated control. The biodegradation of PET films buried in the soil (A), with mangrove plants (B), and bioaugmented with a bacterial consortium (C) was also investigated. The experiments were conducted for 270 days at ambient conditions. The results revealed no difference between treatments in the degradation, with a maximum weight loss of 0.118 % in the bioaugmented treatment. Nevertheless, Scanning Electron Microscope (SEM) and FTIR results indicated significant surface changes, spectral peak shifts, and stretches in PET chemical structures. Bacterial consortia isolated from the soil of the experimental treatments were assessed for degradation of PET monomers, TPA and monoethylene glycol (MEG), and intermediate Bis(2-hydroxyethyl) terephthalate (BHET). The consortia were inoculated in flasks containing minimal media with 1000 mg/L TPA or BHET or1113 mg/L MEG as the sole carbon source. Results showed complete degradation of TPA and significant degradation of BHET (96.09%), and MEG (83.65%) by the consortia. In the second part of the study, bacteria were isolated from various environmental samples and screened for PHA production using Sudan Black B staining on colonies and smeared glass slides. Transmission Electron Microscope images were captured to confirm the intracellular PHA inclusions. A total of 35 isolates were screened for PHA, and 22 showed positive staining. The isolate showing higher levels of PHA synthesis (EC2-30-3) was identified based on 16S rRNA gene sequence as Bacillus sp. and selected for PET monomers degradation and fermentation cultures for PHA production. It was cultured in minimal (Moreira et al., 2013) media with 1000 mg/L TPA and 1113 mg/L MEG as the carbon source for eight days. The isolate grew better in media containing MEG, which was selected as a substrate model for PHA fermentation. To integrate PET monomers biodegradation and production of PHA, the isolate was cultured in 0.2 % MEG. A control with 0.2 % of glucose was prepared, and the cultures were incubated for 96 hours. Bacillus sp. EC2-30-3 showed higher PHA accumulation in media supplied with MEG (40.31%) than glucose (25.53%). This is the first report showing that Bacillus sp. uses PET monomer as carbon source to produce a biopolymer. FTIR results of the extracted PHA identified its functional units as C–H, CH3, C=O, and C–O groups. The absorption bands obtained are closely related to the structure of PHB. The study thus confirmed the ability of the isolated bacteria to degrade PET monomers and produce biopolymers. The results of this work open the possibility for upscaling the use of bacteria to mitigate the impact of PET on the environment while producing environmentally friendly bioplastics
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In the last few years, the tourism industry has experienced rapid expansion and diversification, making it one of the fastest-growing financial industries in the world. Consequently, the hotel industry has significantly affected the environment's long-term viability. Many hotels have begun voluntarily implementing environmentally sustainable practices as they become more aware of their ecological footprint. There has been a great deal of discussion about the effects of hotel operations on the environment and tourism sustainability in Macau. It is because of these negative impacts that hoteliers have adopted green practices in an attempt to minimize them. By developing sustainability reports, hotels can set goals, measure performance, and manage change, resulting in better sustainability. It could also be viewed as a strategy to enhance the company’s sustainability reporting to ensure stakeholders know what the company does. The objective of this study is twofold based on the analysis of the official sustainability reports of four major hotel chains. Firstly, seven categories of sustainable practices effectively adopted by these chain hotels are identified and clusterized. Second, it is presented in which areas some hotels performed more efficiently than others, considering the UN Sustainable Development Goals (SDGs) as a reference. The results allow a comprehensive clusterized analysis of the industry in a highly developed gaming and entertainment area of South China and create a clear comparison between relevant players and their concerns about sustainability practices.
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This chapter presents a systematic review of research on human resources management (HRM) and employee relations (ER) in Angola to identify the main challenges and opportunities presented. To achieve that goal, this chapter characterises research conducted in the country, investigates its main findings, and proposes some directions for the future. Based on a bibliographic search in the EBSCO Discovery database of empirical articles about HRM and ER in Angola, we collected a sample of 28 studies published between 2009 and 2022. Most studies have focused on the development and retention of human resources. Other topics included diversity management, workplace attitudes and behaviours, scale validations, leadership and decision-making, performance appraisal, quality assessment, corporate social responsibility, and expatriates. We identified three main challenges and opportunities in HRM and ER in Angola. First, the policies and the planning, implementing, and evaluating processes of human resources development and retention strategies should be improved. Second, effective leadership and participation should be promoted while navigating the tensions between autocratic and participative leadership styles. Finally, positive ER and employee well-being should be promoted. Understanding these challenges and opportunities may contribute to the development of human capital in Angola and, ultimately, the country’s socioeconomic development.
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"Cantonese opera (CO) represents an art form that had its golden time in Macao during the mid-twentieth century. CO still has many loyal fans but they mainly are in the older generation. The purpose of this study was to explore if CO is considered a cultural capital heritage in Macao, related to cultural identity and transmitted across generations to support social bonding. Applying a qualitative methodology, a script for exploring participants’ experiences and opinions about CO was designed, and different groups of individuals were recruited for semi-structured interviews and focus groups. The data collected was analysed by a thematic analysis of the verbatim transcripts. Findings show that in the past first contacts with CO happened in family and related social context, mainly during participants’ developing age. However, currently CO is no longer passed on to the next generation. Despite that the young generations acknowledging their cultural identities in CO, mainly in terms of Cantonese culture and Cantonese language, older individuals engaged with CO seemed to perceive their cultural identities more in depth in its history, literacy and music. Actually, engagement is an important factor that generates social bonds. The CO leisure practitioners, no matter young or old, experienced the effects of social bonding during the ritual of enquiry in the process of learning and practising CO. To improve CO’s preservation in Macao, the adoption of strategies such as developing new productions, crossover with other media, innovations in promotion targeting the young audiences, and absorbing audiences in the Great Bay area were proposed. Finally, the potential use of CO as a tool in counselling and community work is discussed. "
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This study presents the intrinsic value of Moody’s Corporation, a leading credit rating agency in the U.S. The results of the valuation were compared to the market value of Moody’s Corporation of the same date. The aim of the research is to provide a perspective to the investors on whether the actual value of the Company was overvalued or undervalued in the market, and how much the volatility of the stock price by the change of some factors. Both qualitative and quantitative analyses were applied in the research. The historical data, economic outlook, and the Company’s strategies were collected to be the metrics to determine the intrinsic value and provide an analysis of the prospects of Moody’s Corporation. Three valuation models were applied in the research to estimate the intrinsic value of the Company’s common stock. The cost of debt, cost of equity, the weighted average cost of capital, and the market risk premium were introduced and calculated in the research as they were the critical components in the valuation process. Since the valuation was based on assumptions and historical data to determine future growth, which indicates that the results could be changed due to uncertain factors. This study demonstrates that there was some discrepancy between the stock’s market price and the intrinsic value per share of Moody’s Corporation as of December 31, 2021
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This dissertation aims to research the need and viability of creating a digital platform that assists the creative processes naturally linked to Visual Merchandising. Through the proposal of a digital platform that works as a co-creative tool for display archives and a co-creative tool for display set-ups through mood boards, we will aim at improving the teamwork in retail and provide a unique, fast-forward platform for information sharing and input under the direction of Visual Departments. Building on rich source materials such as bibliography, scientific papers, news, and articles, and interviewing Visual Merchandisers actively working in the field, we will show the importance of creativity in Luxury Retail and what are the most common challenges in the field that we will propose a solution to. We will focus on the study of concepts, reviewing digital application tools being used by professionals and their best features and improvement opportunities. By gathering this information, we hope to provide accurate insights and information that proves the viability of this proposal and understand what features could serve best the target audience. Finally, we will present a conceptual idea in the form of sketches with functions of this digital application tool to be fully developed in the future and hopefully build a consistent well, designed commercial web-based application
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The purpose of this study is to examine work engagement and mental well-being in Macau, specifically after more than three years of COVID. Examine whether external factors such as emotional support from supervisors, co-workers, and family members have a positive impact on work engagement and mental well-being, and whether the internal factor self-reflection with its three aspects of need for self-reflection, engagement in self-reflection, and insight from self-reflection moderates the relationship between emotional support, work engagement, and mental well-being. The target audience consists of Macau's integrated resort, hospitality, and gaming industry employees. According to the Affective Event Theory (AET), affective events at work generate emotional responses that influence the attitudes and behavior of employees in the workplace. In this study, this theoretical framework was used to clarify the interplay of variables that explain emotional support from supervisors, co-workers, and family members, work engagement, and mental well-being. An online self-response survey (N=325) was used to conduct quantitative and cross-sectional research. There was also a combination of simple random sampling, convenience sampling, and referral sampling. All variables were found to be correlated, and while perceived supervisor support was a significant predictor of all aspects of work engagement and mental well-being, family and co-worker support only predicted certain aspects of these variables. Self-reflection partially moderated the positive effects of certain emotional support on work engagement and mental well-being
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