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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."

This article discusses the new gaming law in Macau with emphasis on the critical aspects concerning the gaming operators, concession regime, and other regulatory obligations.1 Thanks to the gaming liberalization commenced in 2001,2 Macau has experienced tremendous economic growth. The past two decades have seen the rapid development of large-scale integrated resorts, and Macau now ranks among the world's major gaming jurisdictions.3 Policy and regulatory challenges have also emerged along with the growth of the junket-driven VIP business in casinos.4 With the recent amendment of Law No. 16/2001 and the subsequent enactment of Law No. 16/2022, Macau has strengthened the legal underpinnings of its system of gaming regulation to oversee various groups involved in casinos and their industry practices. The present study is among the first to review the scope and impact of the revised gaming law, and associated managerial and operational implications for Macau casinos. Topics covered include policy directions, concession requirements, industry participants, gaming taxes, and fair business practices. This study could provide insights into the “Macau 2.0” project and how casinos are to be operated and managed over the next decade. This article could also provide practical guidance for policy makers charged with formulating gaming policy and regulation in other jurisdictions.

Macao SAR, China is one of the more densely-populated territories in the world, and as such necessarily struggles with Soundscape quality. Nonetheless, the territory has already been identified as a unique location for to function as a Soundscape living lab (Cordeiro et al., 2014), since it has a very small manageable area that includes many types of geographical varieties, from extremely high density urban areas to natural environments with dense vegetation highland or varied water front typologies. In addition, Macao has extremely wide multicultural population with a broad range of subjects that have diverse cultural perceptions and thresholds in regards to sonic cognition. The potential impact of this diversity has already been noticed in both tourism (To & Chung, 2019) and research (Chung et al., 2016). The concept of Soundscape itself is garnering increased awareness as a viable alternative to assess the quality of the sonic environment, of use to policy management and legislation, shown not only by the increasing numbers of scientific articles on the subject (Moscoso et al., 2018), but also by recent international standardisation efforts in measuring it (ISO,2018). In this talk we shall give a preliminary description and illustration of the Soundscape in a territory that is rich in diversity and has huge potential for citizen participation. This includes approaches like noise mapping, sound mapping, Soundwalks, grounded theory efforts for detailed descriptions of the environment and use of alternative objective metrics. We will describe how to use the richness of this gathered data in developing artificial-intelligence algorithms to autonomously assess and predict the evaluation of a given Soundscape based on recordings alone. This goal will alleviate the intense human effort in subjective assessment, and may prove to be an effective and substantial diagnostics tool in planning the soundscape for prospective built environments, functioning not only as an analysis and diagnostics tool, but as a design strategy for a sustainable sonic future.

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%.

In view of the complex marine environment of navigation, especially in the case of multiple static and dynamic obstacles, the traditional obstacle avoidance algorithms applied to unmanned surface vehicles (USV) are prone to fall into the trap of local optimization. Therefore, this paper proposes an improved artificial potential field (APF) algorithm, which uses 5G communication technology to communicate between the USV and the control center. The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios. Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks, the algorithm introduces the concept of dynamic artificial potential field. For the multiple obstacles encountered in the process of USV sailing, based on the International Regulations for Preventing Collisions at Sea (COLREGS), the USV determines whether the next step will fall into local optimization through the discrimination mechanism. The local potential field of the USV will dynamically adjust, and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions. The objective function and cost function are designed at the same time, so that the USV can smoothly switch between the global path and the local obstacle avoidance. The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment, and take navigation time and economic cost into account.

Listening to children’s voices is still not considered an essential part of education in some schools, including many in Asian countries. The authority of schools and teachers is still highly valued under the continued influence of Confucian Heritage Culture in many Asian schools, including a significant number in Macao. Teachers in international schools in Asian countries often experience some difficulties when communicating with young children because of their low English proficiency and the traditional views supported by many parents who grew up with the Confucian Heritage Culture, which encourages children to be quiet in the classroom to be good listeners. This Action research took fifteen months between two school years, 2018- 2019 and 2019-2020, with two groups of four and five-year-old students in a kindergarten classroom. Documentation posters were created for young children to use the next morning to reflect on their learning. The pedagogy of listening and pedagogical documentation from the Reggio Emilia approach were implemented to discover and record young children’s ideas and interests, work with daily documentation posters, and help them reflect on documentation posters to improve their learning and develop their higher-order thinking skills. Photos and videos, observation notes with the children’s comments, documentation posters, and reflective discussions were used as interventions to collect the children’s ideas and record their learning activities. The children learned to use documentation posters to remember, think, share, and improve their learning. The children’s comments from Learning Centres, recess, and reflective discussions were used to examine their understanding of learning and higher-order thinking skills. During one Pilot Cycle and three structured data collection cycles, the children demonstrated improvement in learning for each learning project and development of their thinking skills both with and without the teacher’s support. The children demonstrated higher-order thinking skills more often from Learning Centres and recess when they had to solve problems. They also demonstrated higher-order thinking skills more often during the whole group reflective discussions than in small group reflections, when a bigger number of children joined or when they had enough time to think. The thinking skills when children were reflecting were observed to concentrate on remembering and understanding as they focused on remembering and sharing the previous day’s work. The children’s other higher-order thinking skills did not show an increase in frequency during reflective discussions. However, the children demonstrated active engagement and a range of higher-order thinking skills when the teacher asked openended questions and provided support and comments to help them to connect their learning to their past experiences. Findings indicated that the children’s learning from each Learning Centre showed change and improvement during their play over time according to their interests, indicated by their material use and comments. The research was limited by its small number of participants within their age group due to convenience sampling and the children’s relatively limited ability to demonstrate higher-order thinking skills. This study has shown how teachers could help children use daily documentation posters to develop their learning and thinking skills by visualizing their ideas and the teacher’s important role in supporting children’s learning with active listening and support in the classroom

Macau, Macau Business, MAG, MB, MB Featured, Opinion | Macau wisely looks to mainland China, South-East Asia, and Portuguese-speaking countries, as part of its economic diversification. However, to be a player on the international stage and world-wide market, it must look wider, and, hence, the standard of English in Macau must improve dramatically and urgently.

With water being an essential for life on Earth, it is vital to preserve it and regenerate it, in order to be available for a myriad of uses. Though many types of wastewater management and treatment are available, most rely on high energy input and are therefore not ideal for many circumstances. Constructed wetlands (CW) are an alternative nature-based solution to be applied to wastewater treatment. This study undertakes a Life-Cycle Assessment (LCA) of a CW as a means of wastewater treatment and aims to understand how these systems can be an environmentally conscious alternative. The CW under study is located in a rural mountain area in the north of Portugal. Receives wastewater from a tourism unit and operates with horizontal subsurface. The LCA analyses the CW through the construction, operation (treatment), and composting phases. This approach allows the entire scope of the life cycle to be included, of which, the composting phase has been absent in similar LCA previously undertaken. Analysis focuses on the impact categories: Ozone Layer Depletion Potential, Global Warming Potential, Acidification Potential, Eutrophication Potential and Human Toxicity Potential. Of the five categories, none increase during the treatment phase, and indeed, Acidification Potential, Eutrophication Potential, and Human Toxicity potential all decrease. Ozone Layer Depletion Potential and Global Warming Potential increase significantly during the construction and composting phases respectively. Both can be rationalized, with the former being a result of heavy diesel machinery use in construction and the latter a natural byproduct of composting. The results are net positive and display the ability for CW as a low energy wastewater treatment which can limit environmental impact by choice of construction and composting methodology

A growing focus on God’s mercy and forgiveness emerged in the wake of the recent Pontificates of John Paul II, Benedict XVI, and Francis. Our time with its multiple crises cries for healing, forgiveness, and the experience of God’s mercy. In social, political, and global terms, humanity craves for “lasting peace, born of the marriage of justice and mercy” (John Paul II, 2001, no. 15). The experience of God’s forgiveness, merciful healing and new life has been expressed many times in the Bible. But, theologically, it has never been formulated as directly as in Hosea 11:8, when God’s own heart becomes “turned over”, “converted” following the blaze of his own overwhelming compassion, paving the way for a fundamental spiritual transformation, rooted in forgiveness and mercy, that opens wellsprings of dignity, healing, and new life for all.

The aim of this study is to investigate the influence of leadership styles and organizational cultures to employee’s organizational commitment under the pandemic situation in Macao. The dependent variables comprise of the three dimensions of organizational commitment. Among those three, affective commitment and continuance commitment are considered to be analyzed in this study. The leadership styles concept and organizational cultures are applied as the independent variables. The objectives are achieved using quantitative research method with questionnaires in Likert scale scores. The two significance reveals that laissez-faire leadership style had a positive relationship with continuance organizational commitment (H4) and innovative culture had a positive correlation with continuance organization commitment (H6). Such outcomes were extended to a qualitative study with qualitative approach on discourse analysis to explore the potential factor and a leadership discourse analysis was initiated. While the findings on influence of leadership and culture on organizational commitment is not a major concern for Macao employees in the pandemic situation, the significance of specific leadership style and culture rationalizes the transformation and status of Macao employees’ views towards leadership and employers’ perspective on organizational culture. The data collected in this study may also provide valuable resources for future study and training programs for the coming batch of employees in the coming new phase of Macao in entering the 2nd round of gaming licensing. Create the right leadership and culture for the organization to bring back the passion of Macao employees

Corporate leaders are constantly dealing with stress in parallel with continuous decision-making processes. The impact of acute stress on decision-making activities is a relevant area of study to evaluate the impact of the decisions made, and create tools and mechanisms to cope with the inevitable exposure to stress and better manage its impact. The intersection of leadership and neurosciences techniques is called Neuroleadership. In this work, an experiment is proposed to detect and measure the emotional arousal of two groups of business professionals, divided into two groups. The first one is the intervention/stress group, n=30, exposed to stressful conditions, and the control group, n=14, not exposed to stress. The participants are submitted to a sequence of computerized stimuli, such as watching videos, answering survey questions, and making decisions in a realistic office environment. The Galvanic Skin Response (GSR) biosensor monitors emotional arousal in real-time. The experiment design implemented stressors such as visual effects, defacement, unfairness, and time-constraint for the intervention group, followed by decision-making tasks. The results indicate that emotional arousal was statistically significantly higher for the intervention/stress group, considering Shapiro and Mann-Whitney tests. The work indicates that GSR is a reliable stress detector and may be useful to predict negative impacts on executive professionals during decision-making activities.

We are delighted to present this special issue editorial for Neural Computing and Applications special issue on LatinX in AI research. This special issue brings together a collection of articles that explore machine learning and artificial intelligence research from various perspectives, aiming to provide a comprehensive and in-depth understanding of what LatinX researchers are working on in the field. In this editorial, we will introduce the overarching theme of the special issue, highlight the significance of the selected papers, and offer insights into the contributions made by the authors. The LatinX in AI organization was launched in 2018, with leaders from organizations in Artificial Intelligence, Education, Research, Engineering, and Social Impact with a purpose to together create a group that would be focused on “Creating Opportunity for LatinX in AI.” The main goal is to increase the representation of LatinX professionals in the AI industry. LatinX in AI Org and programs are volunteer-run and fiscally sponsored by the Accel AI Institute, 501(c)3 Non-Profit.