Neuromarketing: Evaluating Consumer Emotions and Preferences to Improve Business Marketing Management - Zeng, Ian Mei; Marques, João Alexandre Lobo (European Conference on Management Leadership and Governance, 2023)
The invention of neuroscience has benefited medical practitioners and businesses in improving their management and leadership. Neuromarketing, a field that combines neuroscience and marketing, helps businesses understand consumer behaviour and how they respond to advertising stimuli. This study aims to investigate the consumer purchase intention and preferences to improve the marketing management of the brand, based on neuroscientific tools such as emotional arousal using Galvanic Skin Response (GSR) sensors, eye-tracking, and emotion analysis through facial expressions classification. The stimuli for the experiment are two advertisement videos from the Macau tea brand “Guanding Teahouse” followed by a survey. The experiment was conducted on 40 participants. 76.2% of participants that chose the same product in the first survey responded with the same choice of products in the second survey. The GSR peaks in video ad 1 measured a total of 60. On the other hand, video ad 2 counted a total of 55 GSR peaks. The emotions in ad1 and ad2 have similar responses, with an attention percentage of 76%. The results showed that ad1 has a higher engagement time of 11.1% and ad2 has 9.6%, but only 19 of the respondent’s conducted engagement in video ad1, and 31 showed engagement in video ad2. The results demonstrated that although ad 1 has higher engagement rates, the respondents are more attracted to video ad 2. Therefore, ad2 has better marketing power than ad 1. Overall, this study bridges the gap of no previous research on measuring tea brand advertisements with the neuroscientific method. The results provide valuable insights for marketers to develop better advertisements and marketing campaigns and understand consumer preferences by personalising and targeting advertisements based on consumers' emotional responses and behaviour of consumers' purchase intentions. Future research could explore advertisements targeting different demographics.
Number: 1

Neuromarketing As A Tool To Measure And Evaluate The Consumer Behaviour Of Guanding Teahouse's Social Media Advertisement - Zeng, Ian Mei; Lobo Marques, Joao Alexandre (Proceedings of the 2023 14th International Conference on E-business, Management and Economics, 2023)
This research aims to evaluate a Macau tea brand's social media advertising effectiveness with neuromarketing tools, including physiological monitoring that can measure emotional arousal. This research bridges the gap of social media marketing on Instagram for brands through the neuromarketing method. Data from 40 respondents were collected with iMotions software using neuroscientific tools. This research uses the stimuli of Guanding Teahouse, a newly established Macau tea brand, to evaluate social media advertising effectiveness. The neuroscientific tools – Galvanic Skin Response (GSR) sensors, Eye-tracking, Facial Expression Analysis (FEA) and emotion analysis are used to do the experiment. The data analysis was drawn from one representative respondent to measure the emotions and attention on the Instagram advertisements. Video 1 recorded 9 GSR peaks and Video 2 recorded 12 GSR peaks, both videos attention is ranging between 96-98 indexes. Results show that advertising videos should focus more on the products than the model. Moreover, the participant is more interested in Video 2, but the effectiveness of advertising is showing a lower focus on the brand and the tea. Future studies should consider comparing the video advertising effectiveness of Instagram stories and Instagram reels to prevent disruption of video on the stories ad.

The Criminalization of Verbal Sexual Harassment in Amending Macao's Criminal Code - Yang, Vincent (Socioeconomic Development Research, 2016)

加拿大網絡安全戰略及法律問題 - , - Yang, Vincent (中國法學- 2013年網絡資訊安全法特刊, 2013)

A review on multimodal machine learning in medical diagnostics - Yan, Keyue; Li, Tengyue; Marques, João Alexandre Lobo; Gao, Juntao; Fong, Simon James; Yan, Keyue; Li, Tengyue; Marques, João Alexandre Lobo; Gao, Juntao; Fong, Simon James (Mathematical Biosciences and Engineering, 2023)
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.
Cc_license_type: cc_by Number: mbe-20-05-382 Primary_atype: Mathematical Biosciences and Engineering Subject_term: Review Subject_term_id: Review

Coping with Merging and Advanced Market Risks - Xia, Harry (International Journal of Economics and Social Science, 2015)

The Future of Macau Aviation Industry: A Long-Term Plan & Development Strategies - Xia, Harry (University of Saint Joseph, 2015)

Computer Literacy Teaching Using Peer Learning and Under the Confucian Heritage Cultural Settings of Macao, China - Wong, Kelvin; Neves, Ana; Negreiros, João (International Conference Educational Technologies, 2017, 2017)
University students in Macao are required to attend computer literacy courses to raise their basic skills levels and knowledge as part of their literacy foundation. Still, teachers frequently complain about the weak IT skills of many students, suggesting that most of them may not be benefiting sufficiently from their computer literacy courses. This research proposes an enhanced framework based on constructivist principles by using peer-tutoring to increase cost effectiveness and to improve student outcomes. Essential to this proposed model is the training of former course graduates as peer-instructors to achieve high quality learning results. At Instituto de Formação Turistica (IFT), a case study was used to evaluate its effectiveness using a qualitative analysis. In Macao, most students have a Confucian Heritage Cultural (CHC) background and the current findings demonstrate that students share more easily their learning difficulties within their group as their interpersonal relationships improve. It is suggested that since CHC cooperative learning is primarily based on bonds, students involved in this 'relationship-first, learning-second' type shared a larger amount of knowledge and social skills, a dual positive outcome. Moreover, English language is a major barrier for the understanding of the teacher’s message to Chinese students. Meanwhile, the negative Western concept of plagiarism is replaced, under the CHC, as the ‘face giving’ and it is directly based on the relationship intensity to 'help friends'. At last, peer-tutors play a key role in the student increase internal motivation regarding the joy of the learning process.

Exploratory Analysis of Project Management Adoption and Maturity Level of IT Companies–A Comparison between Macao and Hengqin - Wong, Ka Seng; Lobo Marques, João Alexandre (Journal of Advanced Management Science, 2023)

Fintech Adoption: A Study of Users in the Guangdong-Macao In-Depth Cooperation Zone in Hengqin (China) - Weng, Chi Lei; Lampo, Alessandro (INTI JOURNAL, 2024)
Intended as an economic and development hub, the Hengqin Cooperation Zone aims to foster collaboration and integration between mainland China, Hong Kong, and Macao, serving as a platform for economic development and innovation among the three regions. The zone's development has increased demand for financial services, often offered through fintech. There is, however, a lack of interoperability between the fintech services currently used in Macao and Hengqin. This may hinder Macao users' adoption of the technology. Thus, our research objective is to identify the factors determining Macao residents' adoption of fintech services in the area and provide insights for service providers, developers, and policymakers. A framework based on the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) was used for this purpose. The responses of 103 Macao residents provided evidence that ease of use significantly and positively impacts the usefulness of the technology. This in turn influences attitudes towards fintech usage. Subjective norms and perceived behavioral control positively impact fintech adoption intentions. The fintech industry and the governments of Macao and Hengqin can work on improving technology's ease of use and usefulness. They can also promote them to Macao users, and provide the resources required for better access to fintech in the zone
Number: 02 Publisher: INTI International University

Impacts of Policies and Infrastructure on the Usage of Electric Vehicles in Macao - Weng Chi Lei; Tai, On Teng (2023)
Publisher: Unpublished

China’s Approach to Sustainable Development in Free Trade Agreements - Wei, Dan; Rafael, Ângelo Patrício (Law and Development Review, 2023)
The question of how to adequately integrate environment and labor provisions in free trade agreements is still a difficult one for both States and academicians. This article explores China’s approach to environment and labor issues in free trade agreements. For reference and comparison, it relies on the European Union’s and the United States’ approaches in their respective FTAs. The article identifies China’s preference for a case-by-case approach to the inclusion of environmental chapters in its FTAs. Additionally, in most FTAs it avoids to include provisions on labor standards. These two preferences represent major divergences from the European Union’s and the United States’ approaches, characterized by inclusion of chapters on environment and labor in all their modern FTAs. The article also finds that China’s FTAs rely solely on consultations and cooperation for the implementation of environmental and labor provisions, within the framework of Joint Committees and avoid the inclusion of civil society mechanisms. Moreover, resolution of disputes relies exclusively on consultations, in a diverse procedure than the one applicable to trade disputes. Despite alignment with the European Union model, this is another major point of divergence with the United States’ model, which applies the same enforcement mechanism for both environment and labor issues and trade issues and includes the possibility of applying sanctions. Finally, the article concludes that China’s options with regards to the treatment of environment and labor concerns in its free trade agreements aligns with both its domestic governance approach and its approach to international cooperation.
Publisher: De Gruyter
Keywords: China; environment and trade; free trade agreements; labor and trade; sustainable development

Influencing Companies’ Green Governance Through the System of Legal Liability for Environmental Infractions in China and Brazil: Lighting the Way Toward BRICS Cooperation - Wei, D.; Rafael, A. P. (BRICS Law Journal, 2023)
Peer-rewieved journal
Number: 2

Implementation of Enterprise Resource Planning for the Supply Chain Management of the Food and Beverage Department at Macao Entertainment Corp - Vai, Fong Tou; Lee, Leanda; Negreiros, Joao (Information Resources Management Journal (IRMJ), 2014)
One of the six gaming concession holders in Macao, Macao Entertainment Corp (MEC)1, undertook to centralize three casino/entertainment properties through utilization of a centralized Enterprise Resource Planning (ERP) in April 2010. The Supply Chain (SC) department was the first to apply the ERP in...
Publisher: IGI Global

The Macau Forum and China's Soft Power in the Making: Training the Elite of the Development Portuguese Speaking Countries" - Tran, Émilie; Matias, José Carlos (China - An International Journal, 2015)

The seminars of the Macao forum: An illustration of China’s soft-power diplomacy towards the Portuguese-speaking countries - Tran, Emilie; Dos Santos, Jose Carlos Matias (China: An International Journal, 2015)
This article reviews the role that the Macao Special Administrative Region (SAR) plays in China’s cultural and public diplomacy through training programmes organised by the Macao Forum and tailored for the elite of the world’s Portuguese-speaking countries (PSCs). It begins with a review of China’s approach to key instruments of its soft-power offensive and strategy towards the developing world, followed by an overview of Beijing’s linkages with each PSC. Formulated as an expression of China’s cultural diplomacy towards the PSCs, the seminars of the Macao Forum serve as a kind of cooperation in which the provider party—rather than delivering tangible goods and services such as food, money, loans or infrastructure—actually offers grey matter in the form of ideas for initiatives in public policies and reforms, in order to foster further economic development and administrative rationalisation. Adding to an intense debate and substantial literature that discuss quantitatively and qualitatively China’s role in and aid provision to Africa, the authors argue that China, through the Macao Forum’s training programmes, courts the developing PSCs by building the capacity of their human capital, targeting in particular those in the public and private sectors who are in a position to implement their ideas.

Impact Assessment of the Macao Forum's Seminars (colloquia) on the Economy and Public Policy-Making in Portuguese Speaking Countries - An Illustration of South-South Cooperation - Tran, Émilie (University of Saint Joseph, 2015)

The Application of Nudge Theory in Ensuring Change Acceptance in the Hospitality-Gaming Industry – A Case Analysis from Macau SAR, China - Tagulao, Thea Clarice Saavedra; Marques, Joao Alexandre Lobo (2022 13th International Conference on E-business, Management and Economics, 2022)
As the rate of change increases exponentially, organizations must adapt quickly to the business landscape's volatility, uncertainty, complexity, and ambiguity (VUCA). As a result, organizations must implement agile strategies and practices to ensure their responsiveness and readiness to any changes brought about by internal or external factors. With a greater number of changes, change agents are tasked with implementing various change management methodologies to ensure that change recipients accept change initiatives. This research will look at one of the methodologies used by change agents, the use of nudges from Thaler and Sunstein's Nudge Theory, which is a subtle intervention to influence an individual's decision-making with the goal of steering them towards a specific desired outcome; and analyze their effectiveness towards the change recipients when implemented. Change agents were interviewed on the application of Nudge Theory to change recipients when managing to change initiatives within their respective organizations. The results indicate that the use of nudges created by the change agents can significantly impact the level of resistance from the change recipients. If used correctly, the Nudge Theory can mitigate change resistance, and the success of a change initiative is higher. But, if change recipients are forced to comply, their resistance will be greater, affecting the organization overall.
0 citations (Crossref) [2023-03-15]
Keywords: Change Initiatives; Change Resistance; Nudge Theory; Organizational Behavior; Organizational Change Management

China-Africa: emerging relations - Sousa, Ivo Carneiro de; Diakite, Ansoumane Douty; Iwaloye, Ojo Olukayode (Saint Joseph Academic Press, 2011)
Meeting Name: China-Africa: New Types of Exchange, Cultural Identity and Emerging Relations in a Globalized World
Keywords: Africa China Congresses; China Africa Congresses; Relations

Medical Information Extraction of Clinical Notes and Pictorial Visualisation of Electronic Medical Records Summary Interface - Singh, Praveen; Chaudhary, Gopal; Lobo Marques, Joao Alexandre (Smart Distributed Embedded Systems for Healthcare Applications, 2023)

Modelling the barriers that are preventing e-commerce to thrive – a case study from Portugal, international journal of business excellence - Silva, Susana Costa e; Machado, Joana Costa; Martins, Carla; Duarte, Paulo; Marques, João Alexandre Lobo (International Journal of Business Excellence, 2021)
The identification of barriers for e-commerce to thrive in specific countries is a topic of great interest. This work proposes two models to study the barriers to B2C e-commerce adoption in Portugal, highlighting obstacles less exploited by previous research: the impact of offline shopping pleasure and the influence of the distance to shopping malls on online shopping intent. An online survey was conducted based on different constructs. A multivariate OLS hierarchical regression was used to analyse the proposed models regarding the intention to buy online and the number of online purchases. The results revealed that customer satisfaction is a strong predictor of intent to buy online and that perceived product risk remains a barrier to e-commerce. Consumers living in high urbanised areas have more propensity to buy online. Helpful information is provided regarding the impact of context, culture, product, and individual barriers, showing that multichannel strategies are best suited for success.
Keywords: E-commerce barriers; Online shopping; Portugal; Retail

Spatial modulation of the hydrological risk at Praia, Cape Verde - Silva, José Lino; Neves, Ana Cristina; Negreiros, João Garrott Marques (IOP Conference Series: Earth and Environmental Science, 2016)
Hydrology modeling became a relevant topic for the Cidade da Praia, Cabo Verde, Africa, due to negative impact risk to local population and its assets. The modeling via Geographical Information Systems (GIS) can help the decision-making process of space occupation and characterization for this type of risk. Under the municipalities of Praia, the phenomenon of flash flood is common, causing soil erosion and landslide. This constitutes a risk for the local habitat, particularly in districts with a lack of strong human infrastructures. To simulate, analyze and generate risk maps using GIS to help this county governance authorities for decision-making, thus, becomes the main aim of this article.
Publisher: IOP Publishing

Hydrological Risk Assessment at Praia, Cape Verde - Silva, Jose Lino; Negreiros, Joao Garrott Marques (International Journal of Environment, Agriculture and Biotechnology, 2017)
Hydrology modeling became a relevant topic for the Cidade da Praia, Cabo Verde, Africa, due to negative impact risk to local population and its assets. The modeling via Geographical Information Systems (GIS) can help the decision-making process of space occupation and characterization for this type of risk. Under the municipalities of Praia, the phenomenon of flash flood is common, causing soil erosion and landslide. This constitutes a risk for the local habitat, particularly in districts with a lack of strong human infrastructures. To simulate, analyze and generate risk maps using GIS to help this county governance authorities for decision-making, thus, becomes the main aim of this article.
Number: 2

Towards an efficient prognostic model for fetal state assessment - Silva Neto, Manuel Gonçalves da; Madeiro, João Paulo do Vale; Marques, João Alexandre Lobo; Gomes, Danielo G. (Measurement, 2021)
Monitoring signals such as fetal heart rate (FHR) are important indicators of fetal well-being. Computer-assisted analysis of FHR patterns has been successfully used as a decision support tool. However, the absence of a gold standard for the building blocks decision-making in the systems design process impairs the development of new solutions. Here we propose a prognostic model based on advanced signal processing techniques and machine learning algorithms for the fetal state assessment within a comprehensive evaluation process. Feature-engineering-based and time-series-based machine learning classifiers were modeled into three data segmentation schemas for CTU-UHB, HUFA, and DB-TRIUM datasets and the generalization performance was assessed by a two-way cross-dataset evaluation. It has been shown that the feature-based algorithms outperformed the time-series ones on data-limited scenarios. The Support Vector Machines (SVM) obtained the best results on the datasets individually: specificity (85.6% ) and sensitivity (67.5%). On the other hand, the most effective generalization results were achieved by the Multi-layer perceptron (MLP) with a specificity of 71.6% and sensitivity of 61.7%. The overall process provided a combination of techniques and methods that increased the final prognostic model performance, achieving relevant results and requiring a smaller amount of data when compared to the state-of-the-art fetal status assessment solutions.
1 citations (Crossref) [2022-09-21]
Keywords: Cardiotocography; Classification; Fetal state assessment; Prognostic model; System design

An Exploratory Study of Macao's Role as an Arbitration Seat and Venue for Sino-Luso Commercial Disputes - Si, Leung Cheok; Diakite, Ansoumane Douty (Revista Opinião Jurídica (Fortaleza), 2023)
Objective: Over the past decade, arbitration has grown in popularity as a method of resolving commercial disputes worldwide. However, this practice is relatively new in Macao SAR. Recently, official plans were announced to make Macao as a seat of arbitration for commercial disputes between China and Portuguese-speaking countries (Hereinafter PSCs). This article is dedicated to explores the possibility of Macao undertaking and implementing such a role. Accordingly, this article addresses the following issues: What are the strengths and weaknesses of Macao as a seat and eventually as venue for hosting international commercial arbitration between Chinese and PSCs entrepreneurs?Methodology: A mixed-method approach of legal doctrinal and empirical research was used in this article. We first included a thorough study of the concept of arbitration followed by analysis of various legal journals and legislations, including Macao, China, and PSCs’ arbitration laws. An empirical research was then used to collect data by surveying and interviewing with both lawyers and arbitration practitioners from Macao, China and PSCs.Results: This article argues that the strength of Macao resides in the similarities between its legal system and that of the China and PSCs and the languages advantage (Chinese and Portuguese both official languages). In spite of this, arbitration is still relatively underutilized in the region, and there is a limited number of arbitrators and legal professionals with bilingual proficiency.Contributions: This article contributes to the identification of the opportunities and challenges that Macao faces in its potential future development as a seat/venue of arbitration between China and the PSCs.
0 citations (Crossref) [2023-02-08] Number: 36
Keywords: China; Macao; arbitraje internacional comercial; international commercial arbitration; participante y anfitrión de arbitraje; países de habla portuguesa; portuguese-speaking countries; seat and venue of arbitration

The Internet in China’s state–society relations: Will Goliath prevail in the chiaroscuro? - Sautedé, Eric (China Information, 2013)
This article explores how state and society relations have been affected by the development of information technology in China over the past 20 years. It argues that despite all the transformative changes that such technology has helped bring about, ?benefits? have to be weighed in terms of both empowerment of society and strengthening of state capacity. Ultimately, the digital challenge has not translated into a weakening of the authoritarian state, and this can be explained by the very nature of the party-state in China and how it has managed to make use of communication tools that prove to be both constructive and divisive.
Publisher: SAGE Publications Ltd

Sustainable Practices in Hotel Chains—A Comparative Analysis of Official Annual Hospitality Sustainable Reports from Listed Companies in Macau SAR, China - Santos, Ana Sofia Kong; Marques, João Alexandre Lobo (New Perspectives and Paradigms in Applied Economics and Business, 2023)
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.
Keywords: Environmentally sustainable practices; Macau hotels; Sustainable development goals (SDGs); Sustainable reports; Tourism industry

Comment on ''Generalized James' effective Hamiltonian method'' - Rosado, W.; Arraut, Ivan (Physical Review A, 2023)
In the paper carried out by Wenjun et al. [Phys. Rev. A 95, 032124 (2017)], a generalization of the James effective dynamics theory based on a first version of the James method was presented. However, we contend that this is not a very rigorous way of deriving the effective third-order expansion for an interaction Hamiltonian with harmonic time-dependence. In fact, here we show that the third-order Hamiltonian obtained by Wenjun et al. is not Hermitian for general situations when we consider time dependence. Its non-Hermitian nature arises from the foundation of the theory itself. In this comment paper, the most general expression of the effective Hamiltonian expanded up to third order is obtained. Our derived effective Hamiltonian is Hermitian even in situations where we have time dependence.
Publisher: American Physical Society

Enhancing Health and Public Health through Machine Learning: Decision Support for Smarter Choices - Rodrigues, Pedro Miguel; Madeiro, João Paulo; Marques, João Alexandre Lobo (Bioengineering, 2023)
In recent years, the integration of Machine Learning (ML) techniques in the field of healthcare and public health has emerged as a powerful tool for improving decision-making processes [...]
Number: 7 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: n/a

Evaluation of ECG Non-linear Features in Time-Frequency Domain for the Discrimination of COVID-19 Severity Stages - Ribeiro, Pedro; Pordeus, Daniel; Zacarias, Laíla; Leite, Camila; Alves Neto, Manoel; Aires Peixoto Jr, Arnaldo; de Oliveira, Adriel; Paulo Madeiro, João; Lobo Marques, Joao Alexandre; Miguel Rodrigues, Pedro (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
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.
Keywords: COVID-19; ECG signals; Non-linear analysis; Statistical analysis

COVID-19 Detection by Means of ECG, Voice, and X-ray Computerized Systems: A Review - Ribeiro, Pedro; Marques, João Alexandre Lobo; Rodrigues, Pedro Miguel (Bioengineering, 2023)
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.
Number: 2 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: COVID-19; artificial intelligence; computerized diagnostic systems; image processing; signal processing

Machine learning-based cardiac activity non-linear analysis for discriminating COVID-19 patients with different degrees of severity - Ribeiro, Pedro; Marques, João Alexandre Lobo; Pordeus, Daniel; Zacarias, Laíla; Leite, Camila Ferreira; Sobreira-Neto, Manoel Alves; Peixoto, Arnaldo Aires; de Oliveira, Adriel; Madeiro, João Paulo do Vale; Rodrigues, Pedro Miguel (Biomedical Signal Processing and Control, 2024)
Objective: This study highlights the potential of an Electrocardiogram (ECG) as a powerful tool for early diagnosis of COVID-19 in critically ill patients with limited access to CT–Scan rooms. Methods: In this investigation, 3 categories of patient status were considered: Low, Moderate, and Severe. For each patient, 2 different body positions have been used to collect 2 ECG signals. Then, from each collected signal, 10 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) were extracted every 1s ECG time-series length to serve as entries for 19 Machine learning classifiers within a leave-one-out cross-validation procedure. Four different classification scenarios were tested: Low vs. Moderate, Low vs. Severe, Moderate vs. Severe and one Multi-class comparison (All vs. All). Results: The classification report results were: (1) Low vs. Moderate - 100% of Accuracy and 100% of F1–Score; (2) Low vs. Severe - Accuracy of 91.67% and an F1–Score of 94.92%; (3) Moderate vs. Severe - Accuracy of 94.12% and an F1–Score of 96.43%; and (4) All vs All - 78.57% of Accuracy and 84.75% of F1–Score. Conclusion: The results indicate that the applied methodology could be considered a good tool for distinguishing COVID-19’s different severity stages using ECG signals. Significance: The findings highlight the potential of ECG as a fast and effective tool for COVID-19 examination. In comparison to previous studies using the same database, this study shows a 7.57% improvement in diagnostic accuracy for the All vs All comparison.
Keywords: Accuracy; COVID-19; ECG signals; Machine learning classifiers; Non-linear analysis; –

Quality of Life in Macau, China - Rato, Ricardo; Davey, Gareth (Social Indicators Research, 2012)
We report the initial findings of an ongoing, long-term investigation into subjective quality of life in Macau, a Special Administrative Region of China. Data were collected via quarterly public surveys (2007 to 2009; n = 8,230), as part of the Macau Quality of Life Report. The main aims of the study were to: (a) ascertain the public’s satisfaction with life and with the regional situation in Macau; (b) confirm the utility of the International Wellbeing Index (IWI) as a measure of subjective life quality; and (c) contribute to ongoing discussion in the literature on quality of life in China. The data indicated moderate levels of personal (PWI = 64.4; range 63–66.7) and national (NWI = 59.7; 57.4–63.7) wellbeing across the study period, which implies that residents in Macau are generally satisfied with life. The lowest scores were reported in the first quarter of 2009, a period of great economic uncertainty in Macau and the world, but were positioned within the normative range. The IWI demonstrated good psychometric performance, consistent with previous studies in China and the West, which confirmed its utility. These findings are discussed in relation to the IWI’s theoretical underpinnings and the literature.
12 citations (Crossref) [2022-09-21]
Keywords: China; International Wellbeing index; Macau; Quality of life

Quality of Work Life in Macau - Rato, Ricardo; Davey, Gareth (Happiness Across Cultures: Views of Happiness and Quality of Life in Non-Western Cultures, 2012)
This chapter explores Quality of Work Life (QWL) in Macau. We investigate the meanings and importance of QWL and its implications in terms of happiness and business performance. Although QWL is central to people’s lives, research on this topic is still in its infancy in Macau. Our interviews revealed three salient themes of QWL: Work context, the perceived benefits and demands of the job; Organization, mainly work environment and factors within the organizational context mediating QWL; and the implications of QWL on overall living and happiness.
Keywords: Gaming Industry; Gaming Revenue; Gaming Section; International Wellbeing Index; Work Context

Barometer of Business Relations between China and Portuguese Speaking Countries: An Economic, Commerical and Cultural Approach - Rato, Ricardo (University of Saint Joseph, 2015)

Facial expression for marketing and consumer behavior: A Bibliometric analysis from 2013-2023 using Data Visualization Tools - Qian, Cheng; Lobo Marques, Joao Alexandre (Proceedings of the 2023 14th International Conference on E-business, Management and Economics, 2023)
The classification of emotions based on facial expressions have been a new topic of research in recent years, especially in marketing and consumer behavior areas. However, there is lack of studies to understand how the research topic is developed in terms of bibliometric data. Therefore, the purpose of this work is to provide a bibliometric analysis of the research on the analysis of facial expressions for marketing and consumer behavior, identifying the state of the art, the latest research direction, and other indicators. We extracted data from Web of Science (WOS) platform, considering its core database, resulting in a total of 117 articles. The software Vosviewer was used to analyze the data and graphically visualize the results. This study indicates some of the most influential authors citations and coupling analysis in this specific field, identifies journals with the most published articles, and provide trends of the research area based on the analysis of keywords and corresponding number of articles per year. The results shows that 11 articles (9.4%) were cited more than 100 times, and the two most prolific authors published 5 articles, and the two most influential authors are Bouaziz Sofien and Pauly mark(270 citations) in this field. Of the 117 articles retrieved by WOS, more than 70% were published in high impact journals. The bibliometric analysis of the existing work in this study provides a valuable and reliable reference for researchers in this field and makes a reasonable prediction of the research direction trends.
Keywords: Bibliometric analysis; Consumer; Facial expression; Marketing; Research; VOSviewer

Financial Worldwide Crisis: The Anti-Counter Cycle of Australia - Pou, Boey Tang; Trimarchi, Michael; Negreiros, Joao (Journal of the Faculty of Economics and Administrative Sciences, Çankırı Karatekin University, 2013)
If Australia has been subject to major influences by the United States and European countries, why is its economy healthier than their counter partners? What are the economic foundations that underline this anti-counter cycle of financial worldwide crisis from Australia? What are some of the lessons that countries from Europe that have not fared during the current financial worldwide crisis should learn from Australia? The purpose of this paper is to review the present Australian management system. Four changes are identified including embracement of corporate governance, a shift to adopt more R&D activities, a shift to adopt environmental sustainability practices and emerging corporate social responsibility. On the conclusions settings, a recap and recommendation on how Portugal, a member of the PIGS (Portugal, Italy, Greece and Spain) Southern European Countries club forgot to embrace directives that have been applied in Australia, to avoid the actual financial and identity crisis.
Number: 2

"Going through the mist": early career transitions of Chinese Millennial returnees - Porschitz, Emily T.; Guo, Chun; Alves, José (Managing the New Workforce, 2012)

Classification of Severity of COVID-19 Patients Based on the Heart Rate Variability - Pordeus, Daniel; Ribeiro, Pedro; Zacarias, Laíla; Paulo Madeiro, João; Lobo Marques, Joao Alexandre; Miguel Rodrigues, Pedro; Leite, Camila; Alves Neto, Manoel; Aires Peixoto Jr, Arnaldo; de Oliveira, Adriel (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
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.
Keywords: COVID-19; Electrocardiogram (ECG) signal; Heart Rate Variability (HRV) indices; Severity; Signal processing

Training Strategies for Covid-19 Severity Classification - Pordeus, Daniel; Ribeiro, Pedro; Zacarias, Laíla; de Oliveira, Adriel; Marques, João Alexandre Lobo; Rodrigues, Pedro Miguel; Leite, Camila; Neto, Manoel Alves; Peixoto, Arnaldo Aires; do Vale Madeiro, João Paulo (Bioinformatics and Biomedical Engineering, 2023)
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.
Keywords: COVID-19; Electrocardiogram (ECG); Heart Rate Variability (HRV); disease severity classification; signal processing

Evaluating an Enterprise Content Management for the Macao Government Agency - Pong, F.; Whitfield, R.; Negreiros, J. (ENTERprise Information Systems, 2011)
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.
Keywords: Alfresco©; Enterprise Content Management; Macao Government; Open Source Software

Transgenerational Entrepreneurship In Chinese Family Businesses: Proposal For A Model Of Work-Life Synergy - Phillips, Jenny O. L.; Osorio, Arturo E.; Alves, José (2018)
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.
Publisher: Zenodo
Keywords: Chinese family business; family legacy; stewardship; transgenerational entrepreneurship; work-life synergy.

Entrepreneurial Process of SMEs in Macau - Phillips, Jenny O. L.; Oliveira, Nelio (2022 13th International Conference on E-business, Management and Economics, 2022)
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.
0 citations (Crossref) [2023-03-15]
Keywords: Economic diversification; Entrepreneurial process; Government entrepreneurship aids

Open Innovation as Means of Building Social Capital: A Way to Globalization for Traditional SMEs - Phillips, Jenny O. L. (Journal of Strategic Innovation and Sustainability, 2018)
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.
1 citations (Crossref) [2022-09-21] Number: 2
Keywords: Innovation; SMEs; Social Capital; Sustainability

Ritual and the Sacred in Peter Shaffer's Theatre - Phillips, Jenny O. L. (Sacred and the Everyday: Comparative approaches to literature, religious and secular, 2021)

Succession in Chinese family business: transgenerational transmission of social capital in Macao - Phillips, Jenny O. L. (University of Saint Joseph, 2022)
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
Keywords: China Macau (Special Administrative Region); Family-owned business enterprises

A Heart Rate Variability-based Smart Approach to Analyze Frailty in Older Adults - Paulo do Vale Madeiro, João; César Cortez, Arnaldo Aires Peixoto Júnior, Paulo; Alexandre Lôbo Marques, João; Alisson Pessoa Guimarães, Antônio; Hebert da Silva Felix, John (The Smart Computing Review, 2015)
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.

The Emergence of Resources Seeking Chinese Firms’ Specific Advantages in Emerging Market - Ojo, Olukayode Iwaloye; Im, Hong Kei; Adeniyi, Damilola Olarewaju; Gbadamosi, Ayantunji; Alves, Jose; Link to external site, this link will open in a new window; Trimarchi, Michael (Sustainability, 2022)
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.
Num Pages: 8345 Place: Basel, Switzerland Publisher: MDPI AG
Keywords: OLI theory and Chinese firms; emerging markets; ownership advantages; resources seeking MNEs

Is the Belt and Road Initiative in Africa Sustainable? - Nwachukwu, Francis C. (The Journal of the Macau Ricci Institute, 2019)
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.

Identification of Latent Risk Clinical Attributes for Children Born Under IUGR Condition Using Machine Learning Techniques - Nguyen Van, Sau; Lobo Marques, J. A.; Biala, T. A.; Li, Ye (Computer Methods and Programs in Biomedicine, 2021)
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.
2 citations (Crossref) [2022-09-21]
Keywords: ABPM (Ambulatory Blood Pressure Monitoring); HRV (Heart Rate Variability); IUGR (Intrauterine Growth Restriction); Machine Learning

The future of Cosmetics Advertisement Strategy: A Neuromarketing Study using Electrodermal Activity (EDA) as a measure of Emotional Arousal - Neto, Andreia; Lobo Marques, Joao Alexandre (2022 13th International Conference on E-business, Management and Economics, 2022)
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.
Keywords: advertisement; consumer behavior; consumer neurosciences; cosmetics; marketing; neuromarketing

Evaluation of Deterministic Spatial Interpolators with myGeoffice©: The Utah Grasshoppers Case - Negreiros, Joao; Phillips, Jenny O. L. (International Journal of Geology, Agriculture and Environmental Sciences, 2018)
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.

Ten Spatial Problems with myGeoffice© for Teaching Purposes - Negreiros, Joao; Diakite, Ansoumane (Open Journal of Social Sciences, 2019)
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.
0 citations (Crossref) [2022-09-21] Number: 7 Publisher: Scientific Research Publishing

Contemplation on Today’s Digital Education - Negreiros, João; de Fatima Oliveira, Maria (New Contributions in Information Systems and Technologies, 2015)
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.
Keywords: Education; Facebook; Macao; Moodle; Social Networks

Personality and learning styles surrounded by W3 software: The Macao Portuguese school case - Negreiros, João; Baptista, Zelia; Lee, Leanda (Education and Information Technologies, 2014)
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.
Keywords: Escola Portuguesa de Macao (EPM); Felder and Soloman; ILS; MBTI; Myers and Briggs; Web 2.0

Web 2.0 Tool Recommendations for Teachers - Negreiros, Joao Garrott Marques; Lei, Weng Chi (International Journal of Innovation and Research in Educational Sciences, 2019)

Spatial Analysis Techniques Using MyGeoffice®: - Negreiros, João Garrott Marques (IGI Global, 2018)

Microsoft Power BI Desktop for Data Analytics - NEGREIROS, J. Garrott Marques; MARQUES, JA Lobo (Proc. Multidiscip. Acad. Conf, 2019)

COVID-19 Classification Using CT Scans with Convolutional Neural Networks - Motta, Pedro Crosara; Cesar Cortez, Paulo; Lobo Marques, Jao Alexandre (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
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.

Automatic Classification System for Subjects Exposed to Short-Term Stress Based on Facial Expression Analysis and ElectroDermal Activity - Motta, P.; Silva, B.; Furtado, F.; Lobo Marques, J. A. (2022)

The Importance of Readiness for Change, a Leadership Perspective Based on a Case Study in Macau, SAR China - Marques, João; Reis, Joana; Phillips, Jenny O. L.; Diakite, Ansoumane (Journal of Advanced Management Science, 2020)
0 citations (Crossref) [2022-09-21]

EFFECTIVENESS ANALYSIS OF WATERFALL AND AGILE PROJECT MANAGEMENT METHODOLOGIES – A CASE STUDY FROM MACAU'S CONSTRUCTION INDUSTRY - Marques, Joao Alexandre Lobo; Morais, João José Bragança dos Reis; Alves, José; Gonçalves, Marcus (Revista Gestão em Análise, 2023)
The adoption of project management techniques is a crucial decision for corporate governance in construction companies since the management of areas such as risk, cost, and communications is essential for the success or failure of an endeavor. Nevertheless, different frameworks based on traditional or agile methodologies are available with several approaches, which may create several ways to manage projects. The primary purpose of this work is to investigate the adequate project management methodology for the construction industry from a general perspective and consider a case study from Macau. The methodology considered semi-structured interviews and a survey comparing international and local project managers from the construction industry. The interviews indicate that most construction project managers still follow empirical methods with no specific methodology but consider the adoption of traditional waterfall approaches. In contrast, according to the survey, most project managers and construction managers agree that the project's efficacy needs to increase, namely in planning, waste minimization, communication increase, and focus on the Client's feedback. In addition, there seems to be a clear indication that agile methodology could be implemented in several types of projects, including hospitality development projects. A hybrid development approach based on the Waterfall and Agile methodologies as a tool for the project management area may provide a more suitable methodology for project managers to follow.
Number: 1
Keywords: PMBOK; agile; construction industry; project management methodologies

IoT-Based Smart Health System for Ambulatory Maternal and Fetal Monitoring - Marques, João Alexandre Lobo; Han, Tao; Wu, Wanqing; Madeiro, João Paulo do Vale; Neto, Aloísio Vieira Lira; Gravina, Raffaele; Fortino, Giancarlo; de Albuquerque, Victor Hugo C. (IEEE Internet of Things Journal, 2021)
The adoption of IoT for smart health applications is a relevant tool for distributed and intelligent automatic diagnostic systems. This work proposes the development of an integrated solution to monitor maternal and fetal signals for high-risk pregnancies based on IoT sensors, feature extraction based on data analytics, and an intelligent diagnostic aid system based on a 1-D convolutional neural network (CNN) classifier. The fetal heart rate and a group of maternal clinical indicators, such as the uterine tonus activity, blood pressure, heart rate, temperature, and oxygen saturation are monitored. Multiple data sources generate a significant amount of data in different formats and rates. An emergency diagnostic subsystem is proposed based on a fog computing layer and the best accuracy was 92.59% for both maternal and fetal emergency. A smart health analytics system is proposed for multiple feature extraction and the calculation of linear and nonlinear measures. Finally, a classification technique is proposed as a prediction system for maternal, fetal, and simultaneous health status classification, considering six possible outputs. Different classifiers are evaluated and a proposed CNN presented the best results, with the F1-score ranging from 0.74 to 0.91. The results are validated based on the diagnosis provided by two specialists. The results show that the proposed system is a viable solution for maternal and fetal ambulatory monitoring based on IoT.
9 citations (Crossref) [2022-09-21] Conference Name: IEEE Internet of Things Journal
Keywords: Artificial intelligence (AI); Biomedical monitoring; Cloud computing; Feature extraction; Fetal heart rate; Internet of Things; Medical diagnostic imaging; Monitoring; convolutional neural networks (CNNs); feature extraction; fetal monitoring; health analytics; maternal monitoring

Artificial Intelligence Prediction for the COVID-19 Data Based on LSTM Neural Networks and H2O AutoML - Marques, Joao Alexandre Lobo; Gois, Francisco Nauber Bernardo; Xavier-Neto, José; Fong, Simon James (Predictive Models for Decision Support in the COVID-19 Crisis, 2020)

Epidemiology Compartmental Models—SIR, SEIR, and SEIR with Intervention - Marques, Joao Alexandre Lobo; Gois, Francisco Nauber Bernardo; Xavier-Neto, José; Fong, Simon James (Predictive Models for Decision Support in the COVID-19 Crisis, 2020)

Forecasting COVID-19 Time Series Based on an Autoregressive Model - Marques, Joao Alexandre Lobo; Gois, Francisco Nauber Bernardo; Xavier-Neto, José; Fong, Simon James (Predictive Models for Decision Support in the COVID-19 Crisis, 2020)

Nonlinear Prediction for the COVID-19 Data Based on Quadratic Kalman Filtering - Marques, Joao Alexandre Lobo; Gois, Francisco Nauber Bernardo; Xavier-Neto, José; Fong, Simon James (Predictive Models for Decision Support in the COVID-19 Crisis, 2020)

Predicting the Geographic Spread of the COVID-19 Pandemic: A Case Study from Brazil - Marques, Joao Alexandre Lobo; Gois, Francisco Nauber Bernardo; Xavier-Neto, José; Fong, Simon James (Predictive Models for Decision Support in the COVID-19 Crisis, 2020)

Prediction for Decision Support During the COVID-19 Pandemic - Marques, Joao Alexandre Lobo; Gois, Francisco Nauber Bernardo; Xavier-Neto, José; Fong, Simon James (Predictive Models for Decision Support in the COVID-19 Crisis, 2020)

Predictive Models for Decision Support in the COVID-19 Crisis - Marques, João Alexandre Lobo; Gois, Francisco Nauber Bernardo; Xavier-Neto, Jose; Fong, Simon James (Springer International Publishing, 2021)
COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.

Artificial neural network-based approaches for computer-aided disease diagnosis and treatment - Marques, João Alexandre Lôbo; Gois, Francisco Nauber Bernardo; Madeiro, João Paulo do Vale; Li, Tengyue; Fong, Simon James (Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data, 2022)
The adoption of computer-aided diagnosis and treatment systems based on different types of artificial neural networks (ANNs) is already a reality in several hospital and ambulatory premises. This chapter aims to present a discussion focused on the challenges and trends of adopting these computerized systems, highlighting solutions based on different types and approaches of ANN, more specifically, feed-forward, recurrent, and deep convolutional architectures. One section is focused on the application of AI/ANN solutions to support cardiology in different applications, such as the classification of the heart structure and functional behavior based on echocardiography images; the automatic analysis of the heart electric activity based on ECG signals; and the diagnosis support of angiogram images during surgical interventions. Finally, a case study is presented based on the application of a deep learning convolutional network together with a recent technique called transfer learning to detect brain tumors using an MRI images data set. According to the findings, the model has a high degree of specificity (precision of 0.93 and recall of 0.94 for images with no brain tumor) and can be used as a screening tool for images that do not contain a brain tumor. The f1-score for images with brain tumor was 0.93. The results achieved are very promising and the proposed solution may be considered to be used as a computer-aided diagnosis tool based on deep learning convolutional neural networks. Future works will consider other techniques and compare them with the one presented here. With the comprehensive approach and overview of multiple applications, it is valid to conclude that computer-aided diagnosis and treatment systems are important tools to be considered today and will be an essential part of the trend of personalized medicine over the coming years.
Keywords: Artificial intelligence; Computer-aided diagnosis and treatment; Deep learning; Medical imaging; Neural networks

Research and Technology Development Achievements During the COVID-19 Pandemic—An Overview - Marques, João Alexandre Lobo; Fong, Simon James; Li, G.; Arraut, Ivan; Gois, F. Nauber Bernardo; Neto, José Xavier (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
At the beginning of 2020, the World Health Organization (WHO) started a coordinated global effort to counterattack the potential exponential spread of the SARS-Cov2 virus, responsible for the coronavirus disease, officially named COVID-19. This comprehensive initiative included a research roadmap published in March 2020, including nine dimensions, from epidemiological research to diagnostic tools and vaccine development. With an unprecedented case, the areas of study related to the pandemic received funds and strong attention from different research communities (universities, government, industry, etc.), resulting in an exponential increase in the number of publications and results achieved in such a small window of time. Outstanding research cooperation projects were implemented during the outbreak, and innovative technologies were developed and improved significantly. Clinical and laboratory processes were improved, while managerial personnel were supported by a countless number of models and computational tools for the decision-making process. This chapter aims to introduce an overview of this favorable scenario and highlight a necessary discussion about ethical issues in research related to the COVID-19 and the challenge of low-quality research, focusing only on the publication of techniques and approaches with limited scientific evidence or even practical application. A legacy of lessons learned from this unique period of human history should influence and guide the scientific and industrial communities for the future.
Keywords: COVID-19; Research cooperation; Research ethics; Scientific research; Technology development

Leadership and Neurosciences - The analysis of emotional arousal during decision-making processes with decision-makers exposed to acute stress - Marques, Joao Alexandre Lobo (European Conference on Management Leadership and Governance, 2023)
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.
Number: 1

Nonlinear characterization and complexity analysis of cardiotocographic examinations using entropy measures - Marques, J.A.L.; Cortez, P.C.; Madeiro, J.P.V.; Albuquerque, V.H.C.; Fong, S.J.; Schlindwein, F.S. (Journal of Supercomputing, 2020)
17 citations (Crossref) [2022-09-21]

Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique - Marques, J. A. Lobo; Cortez, P. C.; Madeiro, J. P. D. V.; Fong, S. J.; Schlindwein, F. S.; Albuquerque, V. H. C. D. (IEEE Access, 2019)
The visual analysis of cardiotocographic examinations is a very subjective process. The accurate detection and segmentation of the fetal heart rate (FHR) features and their correlation with the uterine contractions in time allow a better diagnostic and the possibility of anticipation of many problems related to fetal distress. This paper presents a computerized diagnostic aid system based on digital signal processing techniques to detect and segment changes in the FHR and the uterine tone signals automatically. After a pre-processing phase, the FHR baseline detection is calculated. An auxiliary signal called detection line is proposed to support the detection and segmentation processes. Then, the Hilbert transform is used with an adaptive threshold for identifying fiducial points on the fetal and maternal signals. For an antepartum (before labor) database, the positive predictivity value (PPV) is 96.80% for the FHR decelerations, and 96.18% for the FHR accelerations. For an intrapartum (during labor) database, the PPV found was 91.31% for the uterine contractions, 94.01% for the FHR decelerations, and 100% for the FHR accelerations. For the whole set of exams, PPV and SE were both 100% for the identification of FHR DIP II and prolonged decelerations.
13 citations (Crossref) [2022-09-21] Conference Name: IEEE Access
Keywords: Acceleration; Biomedical monitoring; Cardiography; Cardiotocography (CTG); Databases; FHR DIP II; FHR accelerations; FHR baseline detection; FHR decelerations; Fetal heart rate; Hilbert transform; Hilbert transforms; Monitoring; PPV; Transforms; accurate fetal heart rate feature detection; accurate fetal heart rate feature segmentation; adaptive threshold technique; antepartum database; automatic cardiotocography diagnostic system; auxiliary signal; cardiotocographic examinations; computerized diagnostic aid system; digital signal processing techniques; fetal distress; fetal heart rate (FHR); fetal signals; maternal signals; medical signal detection; medical signal processing; obstetrics; patient monitoring; positive predictivity value; preprocessing phase; segmentation processes; uterine contractions; uterine contractions (UC); uterine tone signals; visual analysis

Connecting Neuromarketing and AI - a path to new insights and analysis - Marques, J. A. L. (2023)

Crowdsensing-Based Gamification for Collective Assistance for Post-Era of Coronavirus Epidemic in Community Living - Luo, Renfei; Marques, João Alexandre Lôbo; Ong, Kok-Leong; Fong, Simon (International Journal of Extreme Automation and Connectivity in Healthcare (IJEACH), 2020)
Crowdsensing exploits the sensing abilities offered by smart phones and users' mobility. Users can mutually help each other as a community with the aid of crowdsensing. The potential of crowdsensing has yet to be fully realized for improving public health. A protocol based on gamification to encoura...
0 citations (Crossref) [2022-09-21] Publisher: IGI Global

Exploratory Data Analysis on Clinical and Emotional Parameters of Pregnant Women with COVID-19 Symptoms - Lobo Marques, Joao Alexandre; Macedo, Danielle S.; Motta, Pedro; dos Santos Silva, Bruno Riccelli; Carvalho, Francisco Herlanio Costa; Kehdi, Renata Castro; Cavalcante, Letícia Régia Lima; da Silva Viana, Marylane; Lós, Deniele; Fiorenza, Natália Gindri (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
The scientific literature indicates that pregnant women with COVID-19 are at an increased risk for developing more severe illness conditions when compared with non-pregnant women. The risk of admission to an ICU (Intensive Care Unit) and the need for mechanical ventilator support is three times higher. More significantly, statistics indicate that these patients are also at 70% increased risk of evolving to severe states or even death. In addition, other previous illnesses and age greater than 35 years old increase the risk for the mother and the fetus, including a higher number of cesarean sections, higher systolic and diastolic maternal blood pressure, increasing the risk of eclampsia, and, in some cases, preterm birth. Additionally, pregnant women have more Emotional lability/fluctuations (between positive and negative feelings) during the entire pregnancy. The emotional instability and brain fog that takes place during gestation may open vulnerability for neuropsychiatric symptoms of long COVID, which this population was not studied in depth. The present Chapter characterizes the database presented in this work with clinical and survey data collected about emotions and feelings using the Coronavirus Perinatal Experiences—Impact Survey (COPE-IS). Pregnant women with or without COVID-19 symptoms who gave birth at the Assis Chateaubriand Maternity Hospital (MEAC), a public maternity of the Federal University of Ceara, Brazil, were recruited. In total, 72 mother-infant dyads were included in the study and are considered in this exploratory analysis. The participants have undergone serological tests for SARS-CoV-2 antibody detection and a nasopharyngeal swab test for COVID-19 diagnoses by RT-PCR. A comprehensive Exploratory Data Analysis (EDA) is performed using frequency distribution analysis of multiple types of variables generated from numerical data, multiple-choice, categorized, and Likert-scale questions.

Computerized Systems for Diagnosis and Treatment of COVID-19 - Lobo Marques, Joao Alexandre; Fong, Simon James (Springer International Publishing, 2023)
Keywords: Artificial Intelligence; Biofeedback; Computerized Diagnostic Support; Covid-19; Signal and Image Processing

Technology Developments to Face the COVID-19 Pandemic: Advances, Challenges, and Trends - Lobo Marques, Joao Alexandre; Fong, Simon James (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
The global pandemic triggered by the Corona Virus Disease firstly detected in 2019 (COVID-19), entered the fourth year with many unknown aspects that need to be continuously studied by the medical and academic communities. According to the World Health Organization (WHO), until January 2023, more than 650 million cases were officially accounted (with probably much more non tested cases) with 6,656,601 deaths officially linked to the COVID-19 as plausible root cause. In this Chapter, an overview of some relevant technical aspects related to the COVID-19 pandemic is presented, divided in three parts. First, the advances are highlighted, including the development of new technologies in different areas such as medical devices, vaccines, and computerized system for medical support. Second, the focus is on relevant challenges, including the discussion on how computerized diagnostic supporting systems based on Artificial Intelligence are in fact ready to effectively help on clinical processes, from the perspective of the model proposed by NASA, Technology Readiness Levels (TRL). Finally, two trends are presented with increased necessity of computerized systems to deal with the Long Covid and the interest on Precision Medicine digital tools. Analyzing these three aspects (advances, challenges, and trends) may provide a broader understanding of the impact of the COVID-19 pandemic on the development of Computerized Diagnostic Support Systems.

Epidemic analytics for decision supports in COVID19 crisis - Lobo Marques, Joao Alexandre; Fong, Simon (Springer, 2022)
Covid-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting against the virus, enormously tap on the power of AI and its data analytics models for urgent decision supports at the greatest efforts, ever seen from human history. This book showcases a collection of important data analytics models that were used during the epidemic, and discusses and compares their efficacy and limitations. Readers who from both healthcare industries and academia can gain unique insights on how data analytics models were designed and applied on epidemic data. Taking Covid-19 as a case study, readers especially those who are working in similar fields, would be better prepared in case a new wave of virus epidemic may arise again in the near future.

AI and deep learning for processing the huge amount of patient-centric data that assist in clinical decisions - Lôbo Marques, João Alexandre; Bernardo Gois, Francisco Nauber; Nunes da Silveira, Jarbas Aryel; Li, Tengyue; Fong, Simon James (Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data, 2022)
The area of clinical decision support systems (CDSS) is facing a boost in research and development with the increasing amount of data in clinical analysis together with new tools to support patient care. This creates a vibrant and challenging environment for the medical and technical staff. This chapter presents a discussion about the challenges and trends of CDSS considering big data and patient-centered constraints. Two case studies are presented in detail. The first presents the development of a big data and AI classification system for maternal and fetal ambulatory monitoring, composed by different solutions such as the implementation of an Internet of Things sensors and devices network, a fuzzy inference system for emergency alarms, a feature extraction model based on signal processing of the fetal and maternal data, and finally a deep learning classifier with six convolutional layers achieving an F1-score of 0.89 for the case of both maternal and fetal as harmful. The system was designed to support maternal–fetal ambulatory premises in developing countries, where the demand is extremely high and the number of medical specialists is very low. The second case study considered two artificial intelligence approaches to providing efficient prediction of infections for clinical decision support during the COVID-19 pandemic in Brazil. First, LSTM recurrent neural networks were considered with the model achieving R2=0.93 and MAE=40,604.4 in average, while the best, R2=0.9939, was achieved for the time series 3. Second, an open-source framework called H2O AutoML was considered with the “stacked ensemble” approach and presented the best performance followed by XGBoost. Brazil has been one of the most challenging environments during the pandemic and where efficient predictions may be the difference in saving lives. The presentation of such different approaches (ambulatory monitoring and epidemiology data) is important to illustrate the large spectrum of AI tools to support clinical decision-making.
Keywords: Artificial intelligence; Clinical decisions; Computer-aided diagnostic systems; Deep learning; Patient-centric data

Developing Neuromarketing Innovative Research - Lobo Marques, J. A. (2022)

Intelligent Data Fusion System for Assessing and Classifying the Long-Term Effects of Exposure to COVID-19 in Pregnancy (Long Covid): Associated Neurophysiological and Epigenetic Mechanisms and Consequences for Infant Development - Lobo Marques, J. A. (2023)

IoT-based smart health system for ambulatory maternal and fetal monitoring - Lobo Marques, J. A. (2022)

Neuroeconomics Applications Based on Multiple Monitoring Tools. - Lobo Marques, J. A. (2022)

Artificial intelligence and forensic computing - Lobo-Marques, J. Al (Forensic Computing, 2018)

The (non) standardized classroom - the analysis of three different cultures in the higher education systems - Angola, Brazil and Macau SAR, China - Lobo Marques (Disentangled Vision on Higher Education: Preparing the Generation Next, 2023)
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

Stock Market Prediction Using Artificial Intelligence: A Systematic Review of Systematic Reviews - Lin, Coka Chinyang; Marques, Joao Alexandre Lobo (2023)
There are many systematic reviews on predicting stock. However, each of them reveals a different portion of the hybrid AI analysis and stock prediction puzzle. The principal objective of this research was to systematically review and conclude the systematic reviews on AI and stock to provide particularly useful predictions for making future strategies for stock markets. Keywords that would fall under the broad headings of AI and stock prediction were looked up in two databases, Scopus and Web of Science. We screened 69 titles and read 43 systematic reviews which include more than 379 studies before retaining 10 of them.
Keywords: Deep Learning; Long Short-Term Memory (LSTM); Machine Learning; Neural Networks (NN); Support Vector Machines (SVM)

An Exploratory Comparison of Stock Prices Prediction using Multiple Machine Learning Approaches based on Hong Kong Share Market - Lin, Chinyang; Lobo Marques, João Alexandre (Proceedings of the 2023 14th International Conference on E-business, Management and Economics, 2023)
Stock price prediction has always been challenging due to its volatility and unpredictability. This paper performs a preliminary exploratory comparison that utilizes Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) algorithms to forecast the stock market in Hong Kong. It considers a public dataset publicly available and uses feature engineering to extract relevant features. Then, LSTM and SVM algorithms are applied to predict stock prices. Our results show that the proposed machine learning techniques can predict stock prices in Hong Kong's share market with the error metrics presented, and, for this purpose, LSTM achieved better results than SVM, with MSE = 0.0026, RMSE = 0.0508, MAE = 0.0406, and MAPE = 1.325.
Keywords: Long Short-Term Memory (LSTM); Machine Learning; Stock price prediction; Support Vector Machine (SVM); Time-series analysis

Health and Well-Being Education: Extending the SCARF Learning Analytics Model for Identifying the Learner Happiness Indicators - Li, Tengyue; Marques, Joao Alexandre Lobo; Fong, Simon (International Journal of Extreme Automation and Connectivity in Healthcare (IJEACH), 2020)
The use of learning analytics (LA) in real-world educational applications is growing very fast as academic institutions realize the positive potential that is possible if LA is integrated in decision making. Education in schools on public health need to evolve in response to the new knowledge and th...
0 citations (Crossref) [2022-09-21] Publisher: IGI Global

Fast Cluster-learning with Prior Probability from Big Dataset - Li, Tengyue; Fong, Simon; Lobo Marques, Joao Alexandre; Wong, Raymond K. (2018 5th International Conference on Soft Computing & Machine Intelligence (ISCMI), 2018)
Association Rule Mining by Aprior method has been one of the popular data mining techniques for decades, where knowledge in the form of item-association rules is harvested from a dataset. The quality of item-association rules nevertheless depends on the concentration of frequent items from the input dataset. When the dataset becomes large, the items are scattered far apart. It is known from previous literature that clustering helps produce some data groups which are concentrated with frequent items. Among all the data clusters generated by a clustering algorithm, there must be one or more clusters which contain suitable and frequent items. In turn, the association rules that are mined from such clusters would be assured of better qualities in terms of high confidence than those mined from the whole dataset. However, it is not known in advance which cluster is the suitable one until all the clusters are tried by association rule mining. It is time consuming if they were to be tested by brute-force. In this paper, a statistical property called prior probability is investigated with respect to selecting the best out of many clusters by a clustering algorithm as a pre-processing step before association rule mining. Experiment results indicate that there is correlation between prior probability of the best cluster and the relatively high quality of association rules generated from that cluster. The results are significant as it is possible to know which cluster should be best used for association rule mining instead of testing them all out exhaustively.
0 citations (Crossref) [2022-09-21] ISSN: 2640-0146
Keywords: Association Rule Mining; Big Data; Clustering; Clustering algorithms; Data mining; Itemsets; Preprocessing; Prior Probability; Probabilistic logic; Probability distribution

Digital Renminbi: Impacts on Economic Integration of the Greater Bay Area - Lei, Weng Chi; Wang, Xinru (Economics and Finance Readings, 2023)
The degree of economic integration in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), as reflected in the mobility of trade and capital flows, has been strengthened by free trade agreements, but obstacles including border effects, capital controls, differences of exchange rate systems and inadequate cross-regional coordination remain. Digital renminbi (e-CNY) has been tested in Shenzhen, a core GBA city since April 2020. If e-CNY is adopted in the GBA, the area will effectively become a single currency zone. Whether the GBA constitutes an “optimum currency area” (OCA) depends on its degree of economic integration. This paper computes real interest rate differential (RID), uncovered interest rate differential (UID) and deviation from purchasing power parity (PPD) of each regional pair based on data of interest rates, exchange rates and price indexes from 2016M2 to 2022M7. All UID, PPD and RID series have means within about 1 percent point from 0, indicating high degrees of financial integration, real integration and economic integration. With the exception of Guangdong-Macau RID, all series are stationary, implying mean-reverting behavior. Hence, the parities are expected to hold both in the short run and in the long run, which is a condition for an OCA in the GBA. Furthermore, the regression analysis finds that the test launch of e-CNY in Shenzhen (adjusted for the COVID-19 outbreak) has significant impacts on all RIDs, Guangdong-Macau PPD and Hong Kong-Macau PPD. With merely two and a half years of test launch, the introduction of e-CNY already had impacts on overall economic integration in the GBA.
Keywords: Economic development policy; Economic integration; Exchange rate regime; Financial integration; Greater Bay Area; Optimum currency area

Economic Integration in the GBA: a Price-Based Assessment of Real and Financial Integration in the Greater Bay Area - Lei, Weng Chi; Wang, Xinru (2022 13th International Conference on E-business, Management and Economics, 2022)
The Guangdong-Hong Kong-Macau Greater Bay Area (GBA) was first conceptualized in 2016, which aimed to facilitate trade and finance liberalization among the three regions. The trade and financial environment of the GBA is unique. Due to the “one country, two systems” principle, Mainland China, Hong Kong and Macau are considered to be trading partners bounded by WTO rule, but bilateral free trade agreements have been signed between Mainland China and Hong Kong, and between Mainland China and Macau, but not between Hong Kong and Macau. Furthermore, each of the three regions circulates a local currency subject to its own exchange rate policy, with Hong Kong Dollar and Macau Pataca currently pegged to the US Dollar. These affect the mobility of trade and capital flows in the area. Hence, this paper applies the widely-used price-based approach due to Cheung et al. [5] to analyze the degrees of real and financial integration in the GBA based on interest rates, exchange rates, and price indexes data from January, 2016 to November, 2021. The real interest differential (RID), uncovered interest differential (UID) and the deviation from purchasing power parity (PPD) between each regional pair have means that are statistically and economically close to zero, implying high real and financial integration in the GBA. The unit root tests for stationarity also confirm that the time series are mean-reverting, so the economic integration in the GBA in the long run is foreseeable.
0 citations (Crossref) [2023-03-15]
Keywords: Economic development policy; Economic integration; Financial Integration; Greater Bay Area

Impacts of Central Bank Digital Currency on Regional Economic Integration: Evidence from the Greater Bay Area of China - Lei, Weng Chi; Wang, Xinru (The Chinese Economy, 2024)
An increasing number of countries have launched their central bank digital currencies (CBDC) in recent years, but the economic impacts of CBDC adoption are underexplored. To empirically assess how CBDC adoption influences regional economic integration, this paper investigates the Greater Bay Area, where China carried out one of its first digital renminbi pilot programs. The Greater Bay Area provides a good example because the growing acceptance of digital renminbi in the area can potentially mitigate transaction costs and risks due to the exchange rate volatility of the Chinese renminbi, Hong Kong dollar, and Macao pataca. CBDC adoption can lead to greater real and financial integrations by facilitating cross-border trade in goods and services. This paper evaluates deviations from uncovered interest rate parity, purchasing power parity, and real interest rate parity across Guangdong, Hong Kong, and Macao based on monthly interest rate and price data from January 2016 to December 2022. The time series have mean values near zero, which validate the parity conditions and indicate high degrees of financial, real, and economic integrations. The Markov regime-switching regression model identifies three regimes: (1) pre-Covid, (2) post-Covid, and (3) post-CBDC. The Covid-19 outbreak brought lower integration and stability, but the launch of the CBDC restored some of the pre-Covid integration and stability. Regimes 1 and 2 are persistent, and transitions from Regime 3 back to Regime 1 are probable. Hence, this study finds evidence that CBDC adoption improves regional economic integration in the short and long run.
Publisher: Routledge _eprint: https://doi.org/10.1080/10971475.2024.2333124
Keywords: Central bank digital currency; Greater Bay Area; digital renminbi; economic integration; financial integration

COVID-19: Short-Run Impacts of the Pandemic on the Integrated Resort Oligopoly of Macao - Lei, Weng Chi (2021)
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.

Endogenous fragmented technology and optimal offshoring in large civil aircraft production - Lei, Weng Chi (2013)
This paper is motivated by two observations in the large civil aircraft (LCA) industry. (1) Boeing and Airbus are significantly different in the degree of offshoring. (2) The degree of offshoring also changes among different aircraft models. To offer an explanation, this paper focuses on issues related to fragmentation. Existing literature has established the tie between fragmented technology and offshoring. However, it is assumed that production can be fragmented readily and at no cost; and only exogenous global economic factors have impact on the degree of fragmentation. This model distinguishes itself from others by incorporating endogeneity in fragmentation. A final-good firm can spend on R&D specifically for its own fragmented technology. As a result, the final-good firm can optimally choose the portion of components to be offshored. A strategic trade policy model is used to show that the degree of offshoring depends on the firm's own cost of production, the host country's cost of production, the global state of technology as well as the government trade policies. In particular, export subsidy and subsidy on R&D of fragmented technology are shown to be policy substitutes. Keywords: Fragmentation; Offshoring; Outsourcing; Aircraft; Export subsidy; R&D subsidy; Boeing; Airbus JEL classification: F12; F13; F23; L13

The Road to Service Export Diversification: Gambling and Convention in Macao - Lei, Weng Chi (Economics and Finance Readings: Selected Papers from Asia-Pacific Conference on Economics & Finance, 2019, 2020)
This book is a compilation of the best papers presented at the APEF 2019 conference which was held on 25th and 26th July 2019 at the Grand Copthorne Waterfront in Singapore. With a great number of submissions, it presents the latest research findings in economics and finance and discusses relevant issues in today's world. The book is a useful resource for readers who want access to economics, finance and business research focusing on the Asia-Pacific region.

Three Essays on Foreign Trade, Offshoring and International Rivalry - Lei, Weng Chi (University of Washington, 2018)
This dissertation consists of three essays, covering the topics of foreign trade, offshoring and international rivalry. In particular, Chapter 1 analyzes the strategic capacity allocation of an international oligopoly. Because a line of products shares specific inputs that are fixed in the short run, a multiproduct oligopolist faces a capacity constraint in the production. Not being able to produce the desirable quantities to meet demand, an oligopolist strategically allocates its capacity among different products against its rival. If the market were monopolistic, a firm would mainly concern the effective profitability of a product when allocating its capacity and when responding to a capacity expansion. Identical duopolists that compete in a Cournot fashion should have identical capacity allocation. However, in a sequential game, while the Stackelberg leader allocates all its scarce capacity towards the more profitable product, the follower should still allocate some capacity towards the unprofitable product. This matches the observation that Boeing, the incumbent in the large commercial aircrafts (LCA) industry, specializes in smaller planes, while Airbus allocates resources more evenly towards both superjumbo planes and smaller planes. Chapter 2 provides an explanation to the observation that international oligopolists, which are similar in many ways (subject to the same state of technology, have equal market shares, etc.), may engage in significantly different degrees of offshoring. Different from previous studies, which considered fragmentation to be affected by global exogenous factors only, this essay sees fragmentation as an endogenous variable. A firm can invest on R&D of its own fragmentation technology to enable certain degrees of fragmentation, so that offshoring of those fragmented subparts can be achieved. An important implication of endogenous fragmentation is that the government now has a policy alternative to export subsidy. Very often, when export subsidy is prohibited under an FTA, a government has incentive to subsidize fragmentation of a firm, which can stimulate both export and offshoring. Chapter 3 investigates Macao's and Singapore's questionable goal to diversify among two tourism services—gambling and convention. Macao has a cost advantage in gambling while Singapore has a cost advantage in convention. When a city operates as a regional monopoly, the simple multiproduct model shows that it is optimal for a city to diversify in response to an expansion in the markets of the tourism services. If the two cities operate as a Cournot duopoly instead, there will be a higher degree of product differentiation between the cities. Yet, both cities diversify more when there is a market expansion. On the other hand, Osaka is a potential entrant. The three-city model shows that if Osaka's relative cost of producing convention is even lower than Singapore’s, both Macao and Singapore will produce greater proportions of gambling compared to the two-city case. In general, Macao and Singapore respond to Osaka’s rivalry by strategizing their product mixes to avoid head-on competition with Osaka.
Proquest number: 10748981
Keywords: 0501:Economics; Economics; Foreign trade; International rivalry; Offshoring; Social sciences; Strategic capacity allocation

Steps of Greatness: Geopolitics of OBOR, Ed. University of Macau. - Leandro, Francisco José (University of Macau, 2018)

The OBOR geopolitical drive: the Chinese access security Strategy - Leandro, Francisco J. B. S. (The Belt and Road Initiative Law, Economics, and Politics, 2018)

Desafios à unidade geopolítica da lusofonia - Leandro, Francisco da Silva (IDNBrief, 2017)
info:eu-repo/semantics/publishedVersion
Accepted: 2018-05-07T15:45:27Z Publisher: Instituto da Defesa Nacional

Asia-Europe Comparative Studies Research Project(AECSRP) - Leandro, F. J (University of Saint Joseph, 2016)

Lusophony Risks to Be a Heritage with No Future - Leandro, F. J. (AUSTRAL: Brazilian Journal of Strategy & International Relations, 2017)
0 citations (Crossref) [2022-09-21]

The OBOR Global Geopolitical Drive: The Chinese Access Security Strategy - - Leandro, F. J (Law, Economics, and Politics, 2018)

Multi-view convolutional neural network with leader and long-tail particle swarm optimizer for enhancing heart disease and breast cancer detection - Lan, K.; Liu, L.; Li, T.; Chen, Y.; Fong, S.; Marques, J.A.L.; Wong, R.K.; Tang, R. (Neural Computing and Applications, 2020)
8 citations (Crossref) [2022-09-21]

Multi-view Convolution Neural Network with Swarm Search Based Hyperparameter Optimization for Enhancing Heart Disease and Breast Cancer Detection - Lan, K.; Li, T.; Fong, S.; Marques, J.A.L.; Wong, R.K. (5th International Conference on Soft Computing and Machine Intelligence, ISCMI 2018, 2018)
2 citations (Crossref) [2022-09-21]

Acceptance of Insects as Food: An Exploratory Study of Young Consumers in Macau - Lampo, Alessandro; Sun, Hou Tong (Indian Journal of Entomology, 2023)
Substitute foods are increasingly popular to reduce our environmental footprint and promote food security. As the world population is expected to grow and food resources become scarce, insects as food have recently gained attention as a viable alternative. In the present study, a model grounded on the Theory of Planned Behavior (TPB) is proposed and analyzed through structural equation modeling software (SmartPLS) to assess consumers intentions toward insects as food. Except for subjective norm, both attitude and perceived behavioral control were key determinants of intention and, in turn, of actual use behaviour. Despite insects being consumed in nearly 1/4 of the sample (for instance in Chinese medicine), the study found that respondents were on average relatively unwilling to use them as a dietary habit. Also, it appeared that men were more likely to consume insects as food than women. The insights of our study have important implications for practitioners and policymakers seeking to promote sustainable nutritional practices among consumers. This study is particularly relevant for Macau, as the city positions itself as a "UNESCO Creative City of Gastronomy" with the aim to develop internationally a unique and sustainable food image.

The Influence of Society on the Behavioral Intention to Use a Technology: Evidence from the Battery Electric Vehicles Domain - Lampo, Alessandro; Silva, Susana C.; Duarte, Paulo (International Journal of Business Excellence, 2022)

The role of environmental concern and technology show-off on electric vehicles adoption: the case of Macau - Lampo, Alessandro; Silva, Susana C.; Duarte, Paulo (International Journal of Emerging Markets, 2023)
Purpose Research on battery electric vehicles (BEVs) has typically considered environmental concern a key determinant of behavioral intention that leads individuals to prefer electric vehicles. This paper challenges this assumption and argues that technology frameworks may require new variables to capture consumers' preferences. A UTAUT2-based study has been developed to assess the role of environmental concern in the BEVs context and put forward the technology show-off (TS) concept to explain the technology's acceptance. Design/methodology/approach A quantitative and cross-sectional look at behavioral intention is adopted. The study uses structural equation modeling to analyze a sample of 236 Macau residents to determine the relevance of the factors behind the choice to adopt BEVs. Findings The findings indicate that environmental concern and price may be relevant to explain behavioral intention to adopt the BEVs technology. Furthermore, the UTAUT2 framework seems to benefit from adding new variables, with TS playing a pertinent role in explaining technology acceptance. Social implications The findings show that environmental concern fails to build an argument for the shift to full electric mobility and promote the desired behavioral change toward adopting BEVs. Herein lies the necessity to consider new variables that can better describe the characteristics of modern society. Originality/value This paper proposes the TS construct, combining visibility and trialability as significant determinants of behavioral intention to use technology. The study also stresses the need to reconsider the role of environmental concerns' impact on consumer decision-making.

Diffusion of Technologies: Delivering on the Promises of Battery Electric Vehicles - Lampo, Alessandro; Silva, Susana C. (Walking the Talk? MNEs Transitioning Towards a Sustainable World, 2024)
Battery electric vehicles (BEVs) are living up to their claims as consumers choose them more frequently. The increasing demand for sustainable vehicles translates into the global need for specific components, materials, and infrastructures and drives the regulatory frameworks in each country. While BEVs offer environmental benefits and global business opportunities, the technology has not yet gained mainstream acceptance. Thus, this work aims to investigate the characteristics of BEV users and their role in the diffusion of products to larger segments, as this may vary from country to country. For this purpose, a survey based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) (Venkatesh et al., 2012) framework and structural equation modeling (SmartPLS) was adopted. The results indicated that, except for the constructs of effort expectancy (EE) and social influence (SI), the predictors in the model performed well in this context. Current users are satisfied with their vehicles and are supportive of BEVs in the future. The analysis also revealed that in addition to the availability of financial resources, early adopters are attracted by new technologies in a way that leads them to make decisions outside of the traditional influence of the other members of society. It is suggested to leverage the perceived benefits of status, differentiation, or uniqueness motives, to appeal to those seeking to appear trendy and tech-savvy in society. Companies and policymakers should acknowledge the peculiarities of early customers in their communication strategies to reach a wider audience around the globe and encourage the adoption of BEV technology.
Keywords: Air quality; Battery electric vehicles; Clean energy technology; Consumer behavior; Diffusion of innovations; Early adopters; International marketing

Environmental Concern and the Intention to Use Eco-friendly Technologies: An Analysis of Battery Electric Vehicles in Macau. - Lampo, Alessandro; Silva, Susana C. (Proceedings of the 2023 14th International Conference on E-business, Management and Economics, 2023)
A growing number of people are becoming aware of the environmental footprint that our actions have on the environment. Research indicates that a key factor leading to the adoption of an electric vehicle is consumers’ high environmental concern. Indeed, the environmental concern (EC) construct is commonly associated with the purchase of sustainable and eco-friendly products in literature. Our study challenges this assumption. We examined how the environmental factor influenced the behavioral intention of Macau residents to adopt battery-electric vehicle (BEV) technology. For this purpose, we conducted a study based on the UTAUT-2 framework and used structural equation modeling (SmartPLS) to analyze the data. As a result, the choice of vehicles did not depend on the consumers’ level of concern. It appeared that consumers strongly perceived the benefits of a cleaner environment, however, when it comes to technology, environmental benefits are nice to have, rather than the primary incentive to purchase BEVs. Researchers should consider the role of environmental concern as a background factor in technology acceptance models, rather than a direct predictor of behavior. It is also recommended that marketers correctly consider this element when developing their product communications strategies, to appeal to the desired segment of customers.
Keywords: BEV; Clean Energy Technology; Environmental Footprint; Macau.; Sustainable Transportation; Technology Acceptance

How Social Influence and Image Impact on the Intention to Use a Technology: A Study from the Battery Electric Vehicle Domain - Lampo, Alessandro; Silva, Susana C. (2022 13th International Conference on E-business, Management and Economics, 2022)
Technology research offers several theories and models to explain how individuals accept and use technology innovations. While these often focus on the technical aspects of the innovation, they tend to downplay the affective component of technology. Recognizing that the adoption of technology is also determined by what it means and represents to the users, this paper aims to fill the gap in the literature by studying the effects of social influence and image on the behavioral intention to adopt a technology. We used structural equation modeling (SmartPLS) to analyze data collected from 238 self-administrated surveys regarding the behavioral intention of Macau residents to use battery electric vehicles. The result showed significant relationships among the variables in the model and depicted the construct of image as a strong factor in the adoption decision. Our findings suggest that social influence may not exhibit substantial impact in the case of innovations in their initial phase and, more importantly, the construct of image could be included as a key predictor of behavioral intention in technology acceptance models, particularly in contexts where the choices that consumers make are public, and therefore subject to judgments from the members of the community.
Best Oral Presentation Award: https://www.usj.edu.mo/en/news/dr-alessandro-lampo-receives-best-oral-presentation-award-at-the-iceme-2022/
Keywords: Battery Electric Vehicles; Image; SmartPLS; Social Influence; Technology Acceptance

The Influence of Society on the Behavioral Intention to Use a Technology: Evidence from the Battery Electric Vehicles Domain - Lampo, Alessandro; Silva, Susana C. (Proceedings of the 50th European Marketing Academy (EMAC), 2021)
Despite the general good intentions towards the environment, individuals tend to adopt traditional internal combustion vehicles. Drawing from technology research, this study focuses on the impact of society - in the form of subjective norm and image – on the behavioral intention to adopt a technology. More precisely, this study seeks to explore to which extent societal influences drive the behavioral intention to adopt battery electric vehicles (BEV) technology. A self-administered survey was used for this purpose. The analysis of the data from a sample of 111 respondents showed significant relationships between the predictors and the target behavioral outcome. The study also revealed that subjective norm and image are particularly significant factors for the segment of BEV owners. The findings suggest that marketers and practitioners incorporate social elements into their product communication strategies in order to encourage the uptake of environmentally-sound technologies.

Attitude and perception towards green products in Macao: An exploratory study - Lampo, Alessandro; Leong, Sin U (Society for Global Business and Economic Development, 2014)

Critical development of green marketing in the hotel industry: Macao case study - Lampo, Alessandro; Gregori, Gian Luca; Cardinali, Silvio; Temperini, Valerio (Society for Global Business and Economic Development, 2012)
This study analyzes the green marketing strategies with specific reference to the hotel industry. The concept of green marketing in this sector is crucial due to the growing expected importance of tourism in the future of global economy and its potential impact on social and economic development; this is true particularly in areas with relevant volumes of tourist arrivals. In this sense, we carried out an exploratory research in the hotel industry of the Special Administrative Region (SAR) of Macao in order to: highlight the primary motivations that underlie interventions geared towards the eco-sustainability of hotels, the services they offer and point out the problems, issues, and future prospects in the development of green marketing, as well as explore the role of eco-sustainable values in hotels’ online communication policies. In order to reach these aims a qualitative research was carried out with a semi-structured questionnaire (face-to-face interviews) to a group of hotels. The research was finished by an analysis of their websites, in order to verify possible references to the steps taken to protect the environment.

Macao: A Study on the Impact of Global, Regional and Local Forces. - Lampo, Alessandro; Care, Leanda (Proceedings of the 12th Society for Global Business & Economic Development (SGBED 2011), 2011)
Over the years Macao has been exposed to different cultures and has been influenced by various political and economic interests. The booming casino economy has ultimately transformed the city into the largest gambling hub in the world. In spite of the consensus about Macao's shiny future, there are factors (such as the large reliance on a single industry) and socio-economic problems (such as labor shortage, unequal income distribution, and inflationary pressure) that moderate the optimism. By making use of the Chatterjee and Nankervis' convergent and divergent process model for management, this paper examines how global, regional, and local forces have impacted the economic development process, form and type of organizations in Macao. The paper also suggests that the government implement a framework that develops and diversifies the economy but also takes into consideration the social needs of the community.

Adapting the Unified Theory of Acceptance and Use of Technology 2 (Utaut 2) to Explain Acceptance of Battery Electric Vehicles: Evidence From Macau - Lampo, Alessandro (University of Saint Joseph, 2020)
Vehicles solely powered by electricity are a major technological innovation that combines individual transportation needs and environmental sustainability, yet their market penetration is low. Research has traditionally indicated factors such as the vehicle’s purchasing price, driving range, and charging time as the main barriers to adoption. However, the decision to adopt a technology also depends on what the technology represents to the user; therefore, other factors may be important to explain individuals’ behavior. This study is a quantitative and cross-sectional look at the behavioral intention to adopt battery electric vehicles (BEVs) technology in the context of Macau. The research builds on the unified theory of acceptance and use of technology 2 (UTAUT 2) (Venkatesh et. al., 2012) to explain the characteristics of the local consumers. Besides the addition of image and environmental concern to the theoretical model, the study also put forward and evaluate the construct of technology show-off, an original measure of the visible and experiential characteristics of a technology. A sample of 236 Macau residents was analyzed by structural equation modeling (SEM). The analysis of the data supported the explanatory and predictive power of our model and helped to describe the idiosyncrasies of local residents. The results provide insights related to individual technology acceptance that could be useful in designing more accurate strategies and fostering the uptake of BEVs in Macau or markets that share similarities
Keywords: PhD in Business Administration (D-BA); Thesis and Dissertations; Thesis and Dissertations PhD in Business Administration (D-BA); University of Saint Joseph

AN ANALYSIS OF CRITICAL MANAGERIAL CHALLENGES IN MACAU - Lampo, Alessandro (Revista Gestão em Análise, 2023)
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.
Number: 1
Keywords: Macau; casinos; greater bay area; management; managerial challenges

How is Technology Accepted? Fundamental Works in User Technology Acceptance from Diffusion of Innovations to UTAUT-2 - Lampo, Alessandro (Proceedings of the 8th International Conference on Industrial and Business Engineering, 2023)
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.
Keywords: Acceptance and Use of Technology; Product Innovation; Technology Acceptance; Technology Adoption; Technology Innovation

The Role of Habit in UTAUT-2 Research: A Study of BEV Users - Lampo, Alessandro (Proceedings of the 2023 9th International Conference on Industrial and Business Engineering, 2023)
The UTAUT-2 offers the most comprehensive assessment of individual acceptance and use of technology to date. In particular, the theoretical additions of “hedonic motivation”, “price value”, and “habit”, made the model suitable for studying technology in a consumer context. However, a review of the literature revealed that the construct of habit has been dropped from a large number of studies. There are several reasons for this, including that the technologies examined were relatively new for the respondents to form a routine behavior. Therefore, this study aims to explore whether the construct can be used as a key predictor of future intention to use an innovation rather than an acquired practice among technology users. For this purpose, a conceptual model based on the theoretical additions to the UTAUT-2 is proposed and analyzed with structural equation modeling (SmartPLS). Our results showed significant relationships between the predictors and the behavioral intention to use battery electric vehicles (BEV) technology, and, in particular, depicted the construct of habit as the strongest factor in the decision to adopt the technology. In light of our findings, the construct of habit (HT) should be used in research together with the other UTAUT-2 predictors to assess individuals’ perceptions of possible future habitual behaviors.
Keywords: Battery Electric Vehicles (BEVs); Consumer Behavior; Habit; Process Innovation; Technology Acceptance; UTAUT-2.

Aspects that constitute citizens’ trust in e-government - A review and framework development - Lai, Chimeng; Marques, Alexandre Joao Lobo (Multidisciplinary Reviews, 2024)
The extent of citizens' trust in government determines the success or failure of e-government initiatives. Nevertheless, the idiosyncrasies of the concept and the broad spectrum of its approach still present relevant challenges. This work presents a systematic literature review on e-government trust while elaborating and summarizing a conceptual analysis of trust, introducing evaluation methods for government trust, and compiling relevant research on e-government trust and intentional behavior. A total of 26 key factors that constitute trust have been identified and classified into six categories: Government trust, Trust in Internet and technology (TiIT), Trust in e-government (TiEG), Personal Beliefs, Trustworthiness, and Trust of intermediary (ToI). The value added of this work consists of developing a conceptual framework of TiEG to provide a significant reference for future in-depth studies and research on e-government trust.
Keywords: Systematic Literature Review (SLR); framework; trust; trust in e-government

Investigation on citizen trust towards e-government services in GBA – A study on WeChat and Alipay government service mini-programs - Lai, Chimeng; Joao, Alexandre Lobo Marques (2022 13th International Conference on E-business, Management and Economics, 2022)
Citizens' trust in eGovernment is crucial for the successful implementation of new electronic services. This relationship in the Greater Bay Area (GBA) plays an essential role since the Government services rely on mobile mini-programs This study investigates the trust towards government service mini-programs in WeChat and Alipay. A user feedback questionnaire was designed, and a total of 609 valid samples were collected from Shenzhen, Guangzhou, Hong Kong, and Macau. The findings imply that competence, integrity, and benevolence are the key components of trust in e-government (TIEG). TIEG positively influences perceived value (PV), which positively affects citizens' Intention to adopt service mini-programs. PV significantly mediates the relationship between TIEG and Intention. Although TIEG does not effectively reduce perceived risk (PR), risk issues cannot be ignored in the adoption process. Finally, this article proposes relevant implications and suggestions for the GBA government agents and policy makers.
0 citations (Crossref) [2023-03-15]

Quality of life during the pandemic: a cross sectional study about attitude, individual perspective and behavior change affecting general population in daily life - Khatoon, F.; Kumar, M.; Khalid, A. A.; Alshammari, A. D.; Khan, F.; Alshammari, R. D.; Balouch, Z.; Verma, D.; Mishra, P.; Abotaleb, M.; Makarovskikh, T.; El-kenawy, E. M.; et al. (2022)
Quality of life in general population before and during pandemic is topic need to be address by researcher in terms of mobility, self-care, usual activities, pain/discomfort and anxiety/depression. The study was carried out among Saudi population. Data were collected from general population using questionnaire during the period from 22 August 2021 to 10th January 2022. As a result, total 214 participants have included in this study. Among them prevalent age group include 40 years (n= 63, 29.4%) shadowed by the age group 25-35 (n= 61, 28.5%) while above 60 years group were least frequent (n= 1, 0.5%). On questioning the applicants whether they were satisfied with their health and how would they rate their quality of life, their answers were as follows: yes, or satisfied (n= 86, 40.2%), very Satisfied (n= 102, 47.7%) Dissatisfied (n= 11, 5.1%) and neither satisfied nor dissatisfied (n= 15, 7%). Due to pandemic, they were rate quality of life very good (n= 94, 43.9%), good (n= 63, 29.4 %) poor (n= 5, 2.3 %) and neither good and nor poor (n= 52, 24.3 %). During pandemic 96 participants feel no change in their weight but 110 participants respond that there is increase in coffee intake during the pandemic. Similarly increased in smoking habits and decrease rate in social activities (n=119,41.4%). The psychosomatic well-being of people has been interrupted by disturbing their social activities during pandemic.
Publisher: IET Digital Library

Sustainable Buildings’ Projects – A Perspective from Consultants and Contractors based in Macau SAR, China - J.P.P. Santos, Eduardo; Lobo Marques, Joao; Phyllips, Jenny O. L. (The 2021 12th International Conference on E-business, Management and Economics, 2021)
China growing awareness of sustainability has brought out relevant aspects to move towards a green environment. Since its subscription in 2016, China has been committed to implementing the Paris Agreement, and the Greater Bay Area (GBA) development plan prioritizes ecology and pursuing green development. The primary purpose of this research is to perceive the companies' insights concerning the implementation of sustainable buildings’ projects in Macau. For this multi-case study analysis, primary data was gathered from interviews with two groups involved in the construction projects’ lifecycle: Consultants and Contractors, to analyze different perceptions and concerns. The interviews considered two different themes about the main topic: (1) Perception on Companies’ Experience in Sustainable Projects; (2) Key Drivers towards Sustainable Buildings’ Projects’ Implementation. In conclusion, according to the analyzed data, it is essential to notice that companies’ background and the market particularities affect their corporate performance specially connected to the green construction frameworks. The data also indicate that it is necessary to move towards regulations and policies to change corporate and people's mindset.
0 citations (Crossref) [2022-09-21]
Keywords: Construction industry; Green building; Sustainable Policies; Sustainable building

A Review on Open Innovation and Absorptive Capacity in Small and Medium Enterprises during the last decade - Analyzing Bibliometrics to Understand the Development of the Field - Ip, Chi Hang; Lobo Marques, Joao Alexandre; Dos Santos Silva, Bruno Riccelli; Cortez, Paulo Cesar; Barbosa, Alvaro (Proceedings of the 2023 14th International Conference on E-business, Management and Economics, 2023)
Small and medium-sized enterprises (SMEs) can benefit significantly from open innovation by gaining access to a broader range of resources and expertise using absorptive capacitive, and increasing their visibility and reputation. Nevertheless, multiple barriers impact their capacity to absorb new technologies or adapt to develop them. This paper aims to perform an analysis of relevant topics and trends in Open Innovation (OI) and Absorptive Capacity (AC) in SMEs based on a bibliometric review identifying relevant authors and countries, and highlighting significant research themes and trends. The defined string query is submitted to the Web of Science database, and the bibliometric analysis using VOSviewer software. The results indicate that the number of scientific publications has consistently increased during the past decade, indicating a growing interest of the scientific community, reflecting the industry interest and possibly adoption of OI, considering Absorptive. This bibliometric analysis can provide insights on the most relevant regions the research areas are under intensive development.
Keywords: Absorptive Capacity; Bibliometric analysis; Open innovation; SMEs; VOSviewer

Examining the impact of behavioral factors on the intention of adopting E-government services: An empirical study on the hard-to-reach groups in Macao SAR, China - Iong, Kit Yeng; Phillips, Jenny O. L. (Technology in Society, 2022)
In government studies, electronic government has become a hot topic in recent decades. Many scholars believe that soon, the government might not be able to operate smoothly without the help of ICTs as the Internet has been overwhelming people's daily lives already. In analyzing people's behavioral factors towards adopting e-government services, most studies targeted the adult population, while those in the hard-to-reach groups are minimal. This study was designed especially to understand the behavioral factors of the younger generation aged between 18 and 24 and the senior citizens above 60 on their adoption of e-government services in Macao SAR. Sixteen in-depth interviews were conducted based on the semi-structured interview questions developed from the prior literature on the Theory of Planned Behavior and e-government studies. Six significant findings are yielded, which could serve as an important reference for policymakers designing e-government policy and promoting its implementation strategy. These behavioral factors also contribute empirical data to support the theoretical framework of TPB in the context of Macao SAR e-government services.
0 citations (Crossref) [2022-09-21]
Keywords: Electronic government; Hard-to-reach groups; In-depth interviews; The theory of planned behavior

The transformation of government employees’ behavioural intention towards the adoption of E-government services: An empirical study - Iong, Kit Yeng; Phillips, Jenny O. L. (Social Sciences & Humanities Open, 2023)
Electronic government is increasingly dominant in the study of public administration. In analysing people's behavioural factors towards the adoption of e-services, most previous studies targeted the adult population, while those on government employees are minimal. Government employees have an essential function in the process of government operation; they can be regarded as the principal medium of communication between the service provider (government) and the end-users (citizens). This study was designed to understand the government employees' behavioural factors on their intentions towards adopting e-government services. A set of semi-structured interview questions was developed based on the prior literature on the Theory of Planned Behaviour (TPB) and e-government studies. Ten in-depth interviews were conducted in Macao SAR (Special Administrative Region). In addition to analysing the three primary constructs of TPB, the factor of Trust and some enablers and hindrances were identified. Significant findings were yielded while investigating how the government employees perceived the e-services and how they regarded the general public's perception of this issue. This contextualisation would help policymakers look at this issue from different perspectives and design feasible interventions according to group alignment strategies.
Keywords: Electronic government; Government employees; In-depth interviews; The Theory of Planned Behaviour

Implementation of empowerment in Chinese high power-distance organizations - Humborstad, Sut I W.; Humborstad, Bjarte; Whitfield, Richard; Perry, Chad (The International Journal of Human Resource Management, 2008)
The importance of empowerment in service industries is recognized by practitioners and scholars in the West but there has been limited investigation of its impact on the willingness of service personnel in a high power-distance culture. This study examines how empowerment can be facilitated in the high power-distance context of China. Regression and path model analysis using a sample of 290 service employees from six 4-star to 5-star hotels in the Macau SAR China indicate that empowerment positively leads to higher service willingness and this relationship is mediated by performance-based rewards, and organizational and supervisor support. These findings have implications for HR managers considering or using empowerment.
Publisher: Routledge _eprint: https://doi.org/10.1080/09585190802110224
Keywords: empowerment; high power-distance culture; organizational support; performance-based rewards; supervisor support; training

Burnout and Service Employees' Willingness to Deliver Quality Service - Humborstad, Sut I W; Humborstad, Bjarte; Whitfield, Richard (Journal of Human Resources in Hospitality & Tourism, 2007)
Employees are vital for enhancing customer satisfaction and loyalty in service organizations because their proactive involvement is an essential part of delivering the services offered. With the recent rapid growth of tourism in the Macau SAR, service employee workloads are clearly increasing, and consequently one would expect that the incidence of job burnout is rising. This study uses the well-known Maslach Burnout Inventory (MBI) to investigate the relationship between service employees' burnout and their willingness to deliver quality services. Self-administered questionnaires from 110 operational staff in three hotels in Macau have been analyzed. The results indicate that job burnout reduces staff's willingness to deliver quality services and that this effect is moderated by individual staff's level of affective organizational commitment, and their perceptions of the extent of organizational and supervisor support provided by the organization. Based on these results, practical managerial strategies to improve service performance are identified.
Publisher: Routledge _eprint: https://doi.org/10.1300/J171v07n01_03
Keywords: Job burnout; affective organizational commitment; perceived organizational support; perceived supervisor support; quality service delivery willingness

Neurofinance: Exploratory Analysis Stock Trader's Decision-Making Process by Real-Time Monitoring of Emotional Reactions - Hsu, Hsin-Tzu; Marques, João Alexandre Lobo (European Conference on Management Leadership and Governance, 2023)
Human emotions can be associated with decision-making, and emotions can generate behaviors. Due to the fact that it could be biased and exhaustively complex to examine how human beings make choices, it is necessary to consider relevant groups of study, such as stock traders and non-traders in finance. This work aims to analyze the connection between emotions and the decision-making process of investors and non-investors submitted to the same set of stimuli to understand how emotional arousal might dictate the decision process. Neuroscience monitoring tools such as Real-Time Facial Expression Analysis (AFFDEX), Eye-Tracking, and Galvanic Skin Response (GSR) were adopted to monitor the related experiments of this paper and its accompanying analysis process. Thirty-seven participants attended the study, 24 were classified as stock traders, and 13 were non-traders; the mean age for the groups was 35 and 25, respectively. The designed experiment initially disclosed a thought-provoking result between the two groups under the certainty and risk-seeking prospect theory; there were more risk-takers among non-investors at 75%, while investors were inclined toward certainty at 79.17%. The implication could be that the non-investing individuals were less complex in thought and therefore pursued higher returns besides a high probability of losing the game. In addition, the automatic emotion classification system indicates that when non-investors confronted a stock trending chart beyond their acquaintance or knowledge, they were psychologically exposed to fear, anger, sadness, and surprise. On the contrary, investors were detected with disgust, joy, contempt, engagement, sadness, and surprise, where sadness and surprise overlapped in both parties. Under time pressure conditions, 54.05% of investors or non-investors tend to make decisions after the peak(s) of emotional arousal. Variations were found in the deciding points of the slopes: 2.70% were decided right after the peak(s), 37.84% waited until the emotions turned stable, and 13.51% were determined as the emotional indicators started to slide downwards. Several combinations of emotional responses were associated with decisions. For example, negative emotions could induce passive decision-making, in this case, to sell the stock; nevertheless, it was also examined that as the slope slipped downwards to a particular horizontal point, the individuals became more optimistic and selected the "BUY" option. Future works may consider expanding the study to larger sample size, different demographic groups, and other biometrics for further analysis and conclusions.
Number: 1

Consumers' Adoption of Molecular Chinese Medicine (MCM) in Macau: A Value-based approach - Hong, Chi Kit; Lampo, Alessandro (Proceedings of the 17th International Conference of the Academy of Global Business Research and Practice (AGBRP 2022), 2022)
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.
Best Research Paper Award: https://www.usj.edu.mo/en/news/fbl-student-hong-chi-kit-and-prof-alessandro-lampo-received-the-best-research-paper-award-at-the-17th-international-conference-of-agbrp/

Death of a salesman? the new junket regulation and practice in macau - Ho, Hong-Wai; Phillips, Jenny (Gaming Law Review, 2023)
This review article is among the first to examine the new junket regulations in the Macau gaming industry. Particular emphasis is on the legal and regulatory framework governing the junket activity of gaming promoters and their associates. The recent changes to Macau gaming laws have resulted in stronger licensing requirements for local junket participants and precipitated the collapse of the VIP room system in casinos. Furthermore, this article highlights the policy and managerial implications of the current junket environment for the gaming industry in Macau and possibly other regional gaming jurisdictions. The effects of the new legal environment for Macau junkets could also provide insights into the implementation of similar legislation in other jurisdictions.
Publisher: Mary Ann Liebert, Inc., publishers
Keywords: Macao; VIP room; gambling; gaming regulation; international gaming; junket operation

Macau 2.0: New Gaming Law and its Implications for Casino Market - Ho, Hong-Wai; Phillips, Jenny (Gaming Law Review, 2023)
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.
Publisher: Mary Ann Liebert, Inc., publishers
Keywords: Macao; concession; economic diversification; gaming regulation; junket; operation

Pathophysiological, cardiovascular and neuroendocrine changes in hypertensive patients during the hemodialysis session - Gutiérrez-Adrianzén, O. A.; Moraes, M. E. A.; Almeida, A. P.; Lima, J. W. O.; Marinho, M. F.; Marques, A. L.; Madeiro, J. P. V.; Nepomuceno, L.; da Silva Jr, J. M. S.; Silva Jr, G. B.; Daher, E. F.; Rodrigues Sobrinho, C. R. M. (Journal of Human Hypertension, 2015)
The pathophysiological mechanisms of arterial hypertension during hemodialysis (HD) in patients with end-stage renal disease (ESRD) are still poorly understood. The aim of this study is to investigate physiological, cardiovascular and neuroendocrine changes in patients with ESRD and its correlation with changes in blood pressure (BP) during the HD session. The present study included 21 patients with ESRD undergoing chronic HD treatment. Group A (study) consisted of patients who had BP increase and group B (control) consisted of those who had BP reduction during HD session. Echocardiograms were performed during the HD session to evaluate cardiac output (CO) and systemic vascular resistance (SVR). Before and after the HD session, blood samples were collected to measure brain natriuretic peptide (BNP), catecholamines, endothelin-1 (ET-1), nitric oxide (NO), electrolytes, hematocrit, albumin and nitrogen substances. The mean age of the studied patients was 43±4.9 years, and 54.6% were males. SVR significantly increased in group A (P<0.001). There were no differences in the values of BNP, NO, adrenalin, dopamin and noradrenalin, before and after dialysis, between the two groups. The mean value of ET-1, post HD, was 25.9 pg ml−1 in group A and 13.3 pg ml−1 in group B (P=<0.001). Patients with ESRD showed different hemodynamic patterns during the HD session, with significant BP increase in group A, caused by an increase in SVR possibly due to endothelial dysfunction, evidenced by an increase in serum ET-1 levels.
Number: 6 Publisher: Nature Publishing Group
Keywords: End-stage renal disease; Haemodialysis; Hypertension

Exploring EEG Signal Features for Predicting Post Cardiac Arrest Prognosis - Guilherme Cunha Santos, Antonio; Alexandre Lobo Marques, Joao; Rigo Jr., Luis; Paulo Madeiro, João (2023)

Neuromarketing and Global Branding Reaction Analysis Based on Real-Time Monitoring of Multiple Consumer's Biosignals and Emotions - Goncalves, Marcus; Lobo Marques, Joao Alexandre; Silva, Bruno Riccelli Santos; Luther, Valorie; Hayes, Sydney (Journal of International Business and Management, 2023)
Consumers' selections and decision-making processes are some of the most exciting and challenging topics in neuromarketing, sales, and branding. From a global perspective, multicultural influences and societal conditions are crucial to consider. Neuroscience applications in international marketing and consumer behavior is an emergent and multidisciplinary field aiming to understand consumers' thoughts, reactions, and selection processes in branding and sales. This study focuses on real-time monitoring of different physiological signals using eye-tracking, facial expressions recognition, and Galvanic Skin Response (GSR) acquisition methods to analyze consumers' responses, detect emotional arousal, measure attention or relaxation levels, analyze perception, consciousness, memory, learning, motivation, preference, and decision-making. This research aimed to monitor human subjects' reactions to these signals during an experiment designed in three phases consisting of different branding advertisements. The nonadvertisement exposition was also monitored while gathering survey responses at the end of each phase. A feature extraction module with a data analytics module was implemented to calculate statistical metrics and decision-making supporting tools based on Principal Component Analysis (PCA) and Feature Importance (FI) determination based on the Random Forest technique. The results indicate that when compared to image ads, video ads are more effective in attracting consumers' attention and creating more emotional arousal.

Neuromarketing and Global Branding Reaction Analysis Based on Real-Time Monitoring of Multiple Consumer's Biosignals and Emotions - Goncalves, Marcus V.; Marques, Joao Alexandre Lobo; Silva, Bruno Riccelli Santos; Luther, Valorie; Hayes, Sydney (2022)
Consumers' selections and decision-making processes are some of the most exciting and challenging topics in neuromarketing, sales, and branding. Multicultural influences and societal conditions are also crucial aspects to consider from a global perspective. Applying neuroscience tools and techniques in international marketing and consumer behavior is an emergent and multidisciplinary field that aims to understand consumers' thoughts, reactions, and selection processes in branding and sales. This study focuses on real-time monitoring of different physiological signals using eye-tracking, facial expressions recognition, and Galvanic Skin Response (GSR) acquisition methods to analyze consumers' responses, detect emotional arousal, measure attention or relaxation levels, analyze perception, consciousness, memory, learning, motivation, preference, and decision-making. The primary purpose of this research was to monitor human subjects' reactions to these signals during an experiment designed in three phases consisting of different types of branding advertisements. The non-advertisement exposition was also monitored during the gathering of survey responses at the end of each phase. A feature extraction module was implemented with a data analytics module to calculate statistical metrics and decision-making supporting tools based on Principal Component Analysis (PCA) and Feature Importance (FI) determination based on the Random Forest technique. The results indicate that when compared to image ads, video ads are more effective in attracting consumers' attention and creating more emotional arousal.
Keywords: Branding Reaction; Consumer Biosignal; Galvanic Skin Response; consumer decision-making; eye-tracking; neuromarketing; neurosciences

Intersectoral Linkages in Booming Sector Economies - Gomes, Sérgio Ricardo Santos; Marques, Joao Alexandre Lobo; Reis, Ricardo Ferreira (2022 13th International Conference on E-business, Management and Economics, 2022)

Malaria Blood Smears Object Detection Based on Convolutional DCGAN and CNN Deep Learning Architectures - Gois, Francisco Nauber Bernardo; Marques, João Alexandre Lobo; de Oliveira Dantas, Allberson Bruno; Santos, Márcio Costa; Neto, José Valdir Santiago; de Macêdo, José Antônio Fernandes; Du, Wencai; Li, Ye (Computer and Information Science, 2023)
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.

An exploratory study of students' consumption of non‐alcoholic beverages in Nigeria: A qualitative perspective - Gbadamosi, Ayantunji; Olukayode Iwaloye, Ojo; Bamber, David (Nutrition & Food Science, 2009)
Purpose – Given the diversity which exists among various groups of consumers, the purpose of this paper is to explore students' consumption of non‐alcoholic beverages in Nigeria. Design/methodology/approach – Three focus groups and 20 in‐depth interviews were conducted with students in three universities located in Lagos, Nigeria. Findings – Initial findings indicate that these students' consumption of non‐alcoholic beverages is influenced in many ways. Nevertheless, the most striking of these influences are found to be convenience of purchase, along with availability, price, health concerns, and culture/social reasons. Originality/value – The main contribution of the study lies in the relevance of segmentation, targeting, and positioning activities of business organisations in respect of marketing of non‐alcoholic beverages. Based on the findings, the empirical study will serve as a valuable input to marketers in their planning, analysis, and implementation of appropriate marketing strategies to students vis‐à‐vis the highlighted influences on their consumption of this category of food. It will thus serve as a tool for creating competitive advantage in this prevailing volatile business environment.
Publisher: Emerald Group Publishing Limited
Keywords: Consumer behaviour; Nigeria; Non‐alcoholic drinks; Students

Negative affect among undergraduates: Why are higher levels reported by Asian students?: Negative affect in Asian undergraduates - Found, Andrew; Cheong, Hoi Ieng; Duarte, Carlos (Asia-Pacific Psychiatry, 2012)

Probabilistic Forecasting Model for the COVID-19 Pandemic Based on the Composite Monte Carlo Model Integrated with Deep Learning and Fuzzy System - Fong, Simon James; Marques, João Alexandre Lobo; Li, Gloria; Dey, Nilanjan; Crespo, Rubén González; Herrera-Viedma, Enrique; Gois, Francisco Nauber Bernardo; Neto, José Xavier (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
There are several techniques to support simulation of time series behavior. In this chapter, the approach will be based on the Composite Monte Carlo (CMC) simulation method. This method is able to model future outcomes of time series under analysis from the available data. The establishment of multiple correlations and causality between the data allows modeling the variables and probabilistic distributions and subsequently obtaining also probabilistic results for time series forecasting. To improve the predictor efficiency, computational intelligence techniques are proposed, including a fuzzy inference system and an Artificial Neural Network architecture. This type of model is suitable to be considered not only for the disease monitoring and compartmental classes, but also for managerial data such as clinical resources, medical and health team allocation, and bed management, which are data related to complex decision-making challenges.
Keywords: COVID-19; Composite Monte Carlo simulation; Healthcare decision-making systems; Prediction

The Application of Supervised and Unsupervised Computational Predictive Models to Simulate the COVID19 Pandemic - Fong, Simon James; Marques, João Alexandre Lobo; Li, Gloria; Dey, Nilanjan; Crespo, Rubén González; Herrera-Viedma, Enrique; Gois, Francisco Nauber Bernardo; Neto, José Xavier (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
The application of different tools for predicting COVID19 cases spreading has been widely considered during the pandemic. Comparing different approaches is essential to analyze performance and the practical support they can provide for the current pandemic management. This work proposes using the susceptible-exposed-asymptomatic but infectious-symptomatic and infectious-recovered-deceased (SEAIRD) model for different learning models. The first analysis considers an unsupervised prediction, based directly on the epidemiologic compartmental model. After that, two supervised learning models are considered integrating computational intelligence techniques and control engineering: the fuzzy-PID and the wavelet-ANN-PID models. The purpose is to compare different predictor strategies to validate a viable predictive control system for the COVID19 relevant epidemiologic time series. For each model, after setting the initial conditions for each parameter, the prediction performance is calculated based on the presented data. The use of PID controllers is justified to avoid divergence in the system when the learning process is conducted. The wavelet neural network solution is considered here because of its rapid convergence rate. The proposed solutions are dynamic and can be adjusted and corrected in real time, according to the output error. The results are presented in each subsection of the chapter.
Keywords: ANN predictor; COVID19; Epidemiology; Fuzzy predictor; PID control; SEAIRD

Analysis of the COVID19 Pandemic Behaviour Based on the Compartmental SEAIRD and Adaptive SVEAIRD Epidemiologic Models - Fong, Simon James; Marques, João Alexandre Lobo; Li, G.; Dey, N.; Crespo, Rubén G.; Herrera-Viedma, E.; Gois, F. Nauber Bernardo; Neto, José Xavier (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
A significant number of people infected by COVID19 do not get sick immediately but become carriers of the disease. These patients might have a certain incubation period. However, the classical compartmental model, SEIR, was not originally designed for COVID19. We used the simple, commonly used SEIR model to retrospectively analyse the initial pandemic data from Singapore. Here, the SEIR model was combined with the actual published Singapore pandemic data, and the key parameters were determined by maximizing the nonlinear goodness of fit R2 and minimizing the root mean square error. These parameters served for the fast and directional convergence of the parameters of an improved model. To cover the quarantine and asymptomatic variables, the existing SEIR model was extended to an infectious disease model with a greater number of population compartments, and with parameter values that were tuned adaptively by solving the nonlinear dynamics equations over the available pandemic data, as well as referring to previous experience with SARS. The contribution presented in this paper is a new model called the adaptive SEAIRD model; it considers the new characteristics of COVID19 and is therefore applicable to a population including asymptomatic carriers. The predictive value is enhanced by tuning of the optimal parameters, whose values better reflect the current pandemic.
Keywords: Adaptive SEAIRD model; Adaptive SVEAIRD model; Asymptomatic cases; Prediction models

The Comparison of Different Linear and Nonlinear Models Using Preliminary Data to Efficiently Analyze the COVID-19 Outbreak - Fong, Simon James; Marques, João Alexandre Lobo; Li, G.; Dey, N.; Crespo, Rubén G.; Herrera-Viedma, E.; Gois, F. Nauber Bernardo; Neto, José Xavier (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
The COVID-19 pandemic spread generated an urgent need for computational systems to model its behavior and support governments and healthcare teams to make proper decisions. There are not many cases of global pandemics in history, and the most recent one has unique characteristics, which are tightly connected to the current society’s lifestyle and beliefs, creating an environment of uncertainty. Because of that, the development of mathematical/computational models to forecast the pandemic behavior since its beginning, i.e., with a restricted amount of data collected, is necessary. This chapter focuses on the analysis of different data mining techniques to allow the pandemic prediction with a small amount of data. A case study is presented considering the data from Wuhan, the Chinese city where the virus was first detected, and the place where the major outbreak occurred. The PNN + CF method (Polynomial Neural Network with Corrective Feedback) is presented as the technique with the best prediction performance. This is a promising method that might be considered in future eventual waves of the current pandemic or event to have a suitable model for future epidemic outbreaks around the world.
Keywords: Artificial neural networks; Epidemiology; Machine learning; Prediction models

X-Ray Machine Learning Classification with VGG-16 for Feature Extraction - dos Santos Silva, Bruno Riccelli; Cortez, Paulo Cesar; da Silva Neto, Manuel Gonçalves; Lobo Marques, Joao Alexandre (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
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.

Lung Segmentation of Chest X-Rays Using Unet Convolutional Networks - dos Santos Silva, Bruno Riccelli; Cesar Cortez, Paulo; Gomes Aguiar, Rafael; Rodrigues Ribeiro, Tulio; Pereira Teixeira, Alexandre; Bernardo Gois, Francisco Nauber; Lobo Marques, Joao Alexandre (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
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%.

Covid-19 Detection Based on Chest X-Ray Images Using Multiple Transfer Learning CNN Models - dos Santos Silva, Bruno Riccelli; Cesar Cortez, Paulo; Crosara Motta, Pedro; Lobo Marques, Joao Alexandre (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
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.

Evaluation of mathematical models for QRS feature extraction and QRS morphology classification in ECG signals - do Vale Madeiro, João Paulo; Lobo Marques, João Alexandre; Han, Tao; Coury Pedrosa, Roberto (Measurement, 2020)
It is plausible to assume that the component waves in ECG signals constitute a unique human characteristic because morphology and amplitudes of recorded beats are governed by multiple individual factors. According to the best of our knowledge, the issue of automatically classifying different ’identities’ of QRS morphology has not been explored within the literature. This work proposes five alternative mathematical models for representing different QRS morphologies providing the extraction of a set of features related to QRS shape. The technique incorporates mechanisms of combining the mathematical functions Gaussian, Mexican-Hat and Rayleigh probability density function and also a mechanism for clipping the waveform of those functions. The searching for the optimal parameters which minimize the normalized RMS error between each mathematical model and a given QRS search window enables to find an optimal model. Such modeling behaves as a robust alternative for delineating heartbeats, classifying beat morphologies, detecting subtle and anomalous changes, compression of QRS complex windows among others. The validation process evaluates the ability of each model to represent different QRS morphology classes within 159 full ECG signal records from QT database and 584 QRS search windows from MIT-BIH Arrhythmia database. From the experimental results, we rank the winning rates for which each mathematical model best models and also discriminates the most predominant QRS morphologies Rs, rS, RS, qR, qRs, R, rR’s and QS. Furthermore, the average time errors computed for QRS onset and offset locations when using the corresponding winner mathematical models for delineation purposes were, respectively, 12.87±8.5 ms and 1.47±10.06 ms.
13 citations (Crossref) [2022-09-21]
Keywords: ECG feature extraction; Mathematical modeling; Morphology classification; QRS complex delineation

Evaluating Mathematical Models for Morphological Classification of the QRS Complex - Do Vale Madeiro, J.P.; Barreto, D.; Marques, J.A.L.; Salinet, J.L. (Computing in Cardiology, 2019)

Categorization of Foreign Aid Donors: A Critical Review of the Criteria in Light of China's Reemergence as a Donor - Diakite, Ansoumane Douty; Marques, João Alexandre Lobo (Journal of Global South Studies, 2023)
Over the past several decades, the dichotomy between traditional and emerging donors has been based upon the notion that emerging donors (such as China) support authoritarian regimes and use foreign aid to pursue their economic interests at the expense of the poor in the recipient countries. Accordingly, Western donors, media, and scholars portray Chinese aid as non-poverty-focused. This study aims to review and analyze whether the dichotomy between traditional and emerging donors is still relevant in the current aid system and to propose a new and rigorous criterion for recategorizing donors. In terms of methodology, this study relies on secondary data, including scholarly works on traditional and emerging donors and foreign aid policy documents. Conclusions based on the research indicate that the divide between traditional donors and (re)emerging donors is becoming more ambiguous. The literature review indicates that the two donors’ aids had a mixed impact and that their approaches were similar. This paper highlights the importance of developing different recategorization criteria depending on the impact of aid.
Number: 2
Keywords: China and development assistance committee donors; aid policies; categorization of donors; sustainable development goal; traditional and emerging donors

Arbitration as a dispute resolution method in Macau [Practice Notes] - Diakite, Ansoumane Douty; Cheok, Si Leung (LexisNexis, 2023)
The following Arbitration practice note provides comprehensive and up to date legal information on Arbitration as a dispute resolution method in Macau

Challenging arbitral tribunal jurisdiction in Macau [Practice Notes] - Diakite, Ansoumane Douty (LexisNexis, 2023)
This Practice Note considers challenges to the jurisdiction of arbitral tribunals under the Macau Arbitration Law, the scope of challenge before national courts and tribunals.
Publisher: LexisNexis

China’s Aid policy approach to Poverty Alleviation in the recipient country: A Case study of the Republic of Guinea - Diakite, Ansoumane Douty (Journal of Social Studies (JSS), 2023)
This paper examines the extent to which China’s aid policies integrate poverty alleviation as a goal of their aid in general, particularly in Guinea. More specifically, the paper analyzed how aid donors focus on poverty alleviation and which policies and mechanisms are in place to address poverty in the countries receiving aid. Regarding the methodology, the author collected data from secondary sources, including government declarations of donors, policy documents at both the donor and recipient levels, as well as from scholarly publications. The following findings resulted from study: China’s aid policies have progressively incorporated poverty alleviationobjectives and identified sectors for intervention against poverty. However, the limitations of China approach to poverty is that China adopts a top-down approach to poverty reduction and lacks of an impact evaluation mechanism based on poverty alleviation.
Number: 1
Keywords: Aid policy; China; Guinea; Poverty alleviation; Strategy

Enforcement of arbitral awards in Macau - Diakite, Ansoumane Douty (LexisNexis, 2024)
Under Macau Arbitration Law (MAL, art 64.1), an award shall be made in writing and shall be signed by the arbitrator or arbitrators. Furthermore, the law provides that in case of arbitral proceedings with more than one arbitrator, the signatures of the majority of all members of the arbitral tribunal shall suffice, provided that the reason for any omitted signature is stated (MAL, art 64.2).
Publisher: LexisNexis

Interim remedies in Macau arbitration proceedings [Practice Note] - Diakite, Ansoumane Douty (LexisNexis, 2023)
This Practice Note provides an overview of the powers of tribunals and courts to issue interim remedies including an anti-suit injunction pursuant to the Arbitration Law and the Civil Procedure Code of Macau and provisions dealing with emergency arbitrator appointments pursuant to the Macau Arbitration Law.
Publisher: LexisNexis

Perspectives of Local Communities on the Impact of Chinese Aid: A Case Study of China's Aid Projects in the Education Sector in Guinea - Diakite, Ansoumane Douty (Journal of Globalization Studies, 2023)
China's re-emergence as an aid donor has attracted the attention and criticism from Western donors, academia, and the media. In contrast to traditional donors, China's aid has been portrayed as anti-poverty aid, mainly due to its combination with other instruments, such as investment, and the absence of any political or economic conditions. This paper examines the impact of Chinese aid projects in Guinea's education sector from the perspective of the beneficiaries. The author collected data from both primary (interviews) and secondary (document analysis) sources. The present study concludes that China's aid projects in the education sector have received both positive and negative feedback, mainly because the recipients' needs have not been appropriately targeted. This study contributes to the literature on China's role in Africa. More specifically, it discusses the conditions for aid effectiveness in the field of education. Moreover, in the context of the globalization of aid practices, the study proposes best practices for China to adopt in order to improve the practices of its aid delivery. The novelty of this study lies in the methodology (qualitative method) used to understand China's aid from the perspective of the beneficiaries of its aid.

Motives of Traditional and Emerging Donors in Aid Giving: Comparative Study between China and France - Diakite, Ansoumane D.; Phillips, Jenny O. L. (Journal of Social and Political Sciences, 2019)
Since the beginning of bilateral aid giving in the aftermath of the Second World War, the motives for aid giving have changed from being purely political and humanitarian to a mix of different interests. While poverty reduction is frequently stated as the goal of aid giving, it is commonplace for donors to use aid to advance their national interests. The rise of new, emerging donors is creating discussion in both the political and academic fields of aid giving. Traditional or western donors see emerging donors, such as China’s efforts in aid-giving as seeking the natural resources of the recipient countries. This paper provides a historical analysis of the aid-giving motivations underlying an emerging donor, China, and a traditional donor, France. The motives for China’s and France’s aid giving to African countries, with special focus on Guinea, show a great number of similarities.
1 citations (Crossref) [2022-09-21]
Keywords: Aid Giving Motives; Emerging Donor; Traditional Donor; Poverty Reduction

Aid to Infrastructure Development in Sub Saharan Africa: An Assessment of China Financing Approaches - Diakité, A.D. (China-Africa: New Types of Exchange, Cultural Identity and Emerging Relations in a Globalized World, 2010)

An Exploratory Study on the Possibility of Harmonizing Investment Protection Regimes within the OHADA Zone - Diakité, A. D.; Thiam, A. B. (Transnational Dispute Management (TDM), 2022)
Abstract With its large population and natural resources, Africa needs investors who can sustain its development. At the same time, foreign investors expect returns on their investments. In ...
Publisher: Maris BV

Lead: An iOS Application to Help in the Construction of New Habits - de Aguiar, André Wescley Oliveira; Bezerra, Jagni Dasa Horta; Marques, João Alexandre Lobo; de Alexandria, Auzuir Ripardo (International Journal of Information and Electronics Engineering, 2019)

Macau, Quality of Life - Davey, Gareth; Rato, Ricardo (Encyclopedia of Quality of Life and Well-Being Research, 2014)

Subjective Wellbeing in China: A Review - Davey, Gareth; Rato, Ricardo (Journal of Happiness Studies, 2012)
We critically review studies of subjective wellbeing conducted in China by the International Wellbeing Group, and we evaluate the International Wellbeing Index (IWI), a new instrument they developed. Subjective wellbeing was positive and similar in studies across China, and conformed to the normative range. Its resilience (PWI = 61.2–67.1) mirrors survey findings conducted in Western countries, in agreement with Subjective Wellbeing Homeostasis. Reliability, validity and psychometric analyses support the utility of the IWI as a measure of subjective wellbeing. Our conclusions have implications for research and social development in China, discussed further in this review.
Keywords: China; Happiness; International wellbeing index; Quality of life; Subjective wellbeing

A Prospective analysis about employee retention strategies for Macao Hotel Industry - Chong, Ka Yee; Lobo Marques, Joao A. (The 2021 12th International Conference on E-business, Management and Economics, 2021)
Human resources are essential to the survival, success, and long-term growth of a company. Hotel is an industry requiring a high level of human resources for delivering high-quality personal service to the hotel guests to maintain its competitiveness in the business environment. With the rapid economic growth in Macao started in 2002, all the industries have been growing fast and competing fiercely for the limited manpower in Macao. However, the Macao hotel industry has been losing its attractiveness in the Macao labor market and needs to rely on non-local workers with a limited stay in Macao. The management team of the Macao hotel industry is looking for a solution to maintain a stable workforce. Therefore, a study has been conducted on the effectiveness of its employee retention strategies. A questionnaire was designed to collect the preferences of the employees and interviews were conducted to understand the perspective of the management team toward the employee retention strategies. The study shows the employee strategies are focused on key employees’ interests such as career development and prospect. However, the communication between the management team and employees failed and led to employee turnover.
0 citations (Crossref) [2022-09-21]
Keywords: Employee retention; Employee turnover reasons; Macao hotel industry; Macao shortage of manpower

Nowcasting Gross Domestic Product and Gross Gaming Revenue of Macau: a Theoretical and Conceptual Framework - Chau, Manuel; Lei, Weng Chi (2021)
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.

Management Transition in South Korea: A Case Study - Chan, Wai Ip; Trimarchi, Michael; Negreiros, Joao (Asian Journal of Business and Management Sciences, 2012)
South Korea management system has been influenced significantly by their traditional social and religious beliefs for hundreds of years. Yet, the 1997 Asian financial crisis has gradually confirmed this shifted, from the Confucius mentality to a close Westernized system. This paper aims to evaluate this management transition in South Korea. The theoretical model of the convergent-divergent, as proposed by Chatterjee and Nankervis [2006], is applied to identify a number of critical factors. The aforementioned factors altogether have influenced the management system in four main vectors: (A) From seniority to meritocracy performance management; (B) From consultative to individualistic decision-making style; (C) From ignoring to embracing corporate governance; (D) From avoiding to improving environmental sustainability.

How social media affects the purchase intentions of female consumers in Macao - watching beauty and cosmetics product experience videos on YouTube - Chan, Velda; Silva, Susana C.; Lampo, Alessandro (Revista Gestão em Análise, 2022)
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.
Number: 3
Keywords: YouTube beauty products; YouTube marketing; beauty and cosmetics marketing; purchase intention

Factors influencing disability inclusion practice on social media - Chan, Joye Wai Peng; Phillips, Jenny O.L. (Proceedings of the 2023 14th International Conference on E-business, Management and Economics, 2023)
Digital inclusion in Macao is in the very beginning stage, and disability inclusion practice on social media in producing and promoting accessible social media content and needs is hard to find. This study aims to analyse the factors that influence communication staff's practice of disability inclusion on social media by using the combined employee behaviour and communication process model to provide suggestions to management who wants to promote disability inclusion practice on social media.The Service Centre for the Deaf of the Macau Deaf Association (MDA) was selected as the object for this case study. The online social media used for MDA's communication was analysed, and semi-structured in-depth interviews with members of the Association were conducted. The research findings showed that, except for the reward structure, factors examined from the work environment in terms of organisation, supervision and co-workers; communication staff themselves; outcomes of accessible social media communication; audience and feedbacks show relations with disability inclusion practices on social media. The delivery of inclusive culture, the influential power of disability stakeholders and the positioning of social media platforms are the key influencing factors.The interesting part of this study is that people without disabilities seem to be excluded from the disability inclusion practice carried out on MDA's Facebook. Their social media content is highly accessible to deaf and hard-of-hearing audiences yet seems not to involve the general public. The study object is a good model for producing accessible content, yet the optimisation of promoting social media accessibility needs further exploration.
Keywords: Accessible Social Media (ASM); Disability Employment; Disability Inclusion; Macau Deaf Association

Sudden cardiac death multiparametric classification system for Chagas heart disease's patients based on clinical data and 24-hours ECG monitoring - Cavalcante, Carlos H. L.; Primo, Pedro E. O.; Sales, Carlos A. F.; Caldas, Weslley L.; Silva, João H. M.; Souza, Amauri H.; Marinho, Emmanuel S.; Pedrosa, Roberto C.; Marques, João A. L.; Santos, Hélcio S.; Madeiro, João P. V.; Cavalcante, Carlos H. L.; et al. (Mathematical Biosciences and Engineering, 2023)
About 6.5 million people are infected with Chagas disease (CD) globally, and WHO estimates that $ > 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.
Cc_license_type: cc_by Number: mbe-20-05-402 Primary_atype: Mathematical Biosciences and Engineering Subject_term: Research article Subject_term_id: Research article

Obediência militar, liberdade e consciência, Ética Aplicada: Política, Edições 70, - Carreiras, H.; Leandro, F. J. (2018)

Noise Detection and Classification in Chagasic ECG Signals Based on One-Dimensional Convolutional Neural Networks - Caldas, Weslley Lioba; do Vale Madeiro, João Paulo; Pedrosa, Roberto Coury; Gomes, João Paulo Pordeus; Du, Wencai; Marques, João Alexandre Lobo (Computer and Information Science, 2023)
Continuous cardiac monitoring has been increasingly adopted to prevent heart diseases, especially the case of Chagas disease, a chronic condition that can degrade the heart condition, leading to sudden cardiac death. Unfortunately, a common challenge for these systems is the low-quality and high level of noise in ECG signal collection. Also, generic techniques to assess the ECG quality can discard useful information in these so-called chagasic ECG signals. To mitigate this issue, this work proposes a 1D CNN network to assess the quality of the ECG signal for chagasic patients and compare it to the state of art techniques. Segments of 10 s were extracted from 200 1-lead ECG Holter signals. Different feature extractions were considered such as morphological fiducial points, interval duration, and statistical features, aiming to classify 400 segments into four signal quality types: Acceptable ECG, Non-ECG, Wandering Baseline (WB), and AC Interference (ACI) segments. The proposed CNN architecture achieves a $$0.90 \pm 0.02$$accuracy in the multi-classification experiment and also $$0.94 \pm 0.01$$when considering only acceptable ECG against the other three classes. Also, we presented a complementary experiment showing that, after removing noisy segments, we improved morphological recognition (based on QRS wave) by 33% of the entire ECG data. The proposed noise detector may be applied as a useful tool for pre-processing chagasic ECG signals.
Keywords: Chagas disease; Deep learning; ECG quality assessment

Classification of COVID-19 CT Scans Using Convolutional Neural Networks and Transformers - Bernardo Gois, Francisco Nauber; Lobo Marques, Joao Alexandre; Fong, Simon James (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
COVID-19 is a respiratory disorder caused by CoronaVirus and SARS (SARS-CoV2). WHO declared COVID-19 a global pandemic in March 2020 and several nations’ healthcare systems were on the verge of collapsing. With that, became crucial to screen COVID-19-positive patients to maximize limited resources. NAATs and antigen tests are utilized to diagnose COVID-19 infections. NAATs reliably detect SARS-CoV-2 and seldom produce false-negative results. Because of its specificity and sensitivity, RT-PCR can be considered the gold standard for COVID-19 diagnosis. This test’s complex gear is pricey and time-consuming, using skilled specialists to collect throat or nasal mucus samples. These tests require laboratory facilities and a machine for detection and analysis. Deep learning networks have been used for feature extraction and classification of Chest CT-Scan images and as an innovative detection approach in clinical practice. Because of COVID-19 CT scans’ medical characteristics, the lesions are widely spread and display a range of local aspects. Using deep learning to diagnose directly is difficult. In COVID-19, a Transformer and Convolutional Neural Network module are presented to extract local and global information from CT images. This chapter explains transfer learning, considering VGG-16 network, in CT examinations and compares convolutional networks with Vision Transformers (ViT). Vit usage increased VGG-16 network F1-score to 0.94.

TPOT Automated Machine Learning Approach for Multiple Diagnostic Classification of Lung Radiography and Feature Extraction - Bernardo Gois, Francisco Nauber; Lobo Marques, Joao Alexandre; Fong, Simon James (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
This chapter describes an AUTO-ML strategy to detect COVID on chest X-rays utilizing Transfer Learning feature extraction and the AutoML TPOT framework in order to identify lung illnesses (such as COVID or pneumonia). MobileNet is a lightweight network that uses depthwise separable convolution to deepen the network while decreasing parameters and computation. AutoML is a revolutionary concept of automated machine learning (AML) that automates the process of building an ML pipeline inside a constrained computing framework. The term “AutoML” can mean a number of different things depending on context. AutoML has risen to prominence in both the business world and the academic community thanks to the ever-increasing capabilities of modern computers. Python Optimised ML Pipeline (TPOT) is a Python-based ML tool that optimizes pipeline efficiency via genetic programming. We use TPOT builds models for extracted MobileNet network features from COVID-19 image data. The f1-score of 0.79 classifies Normal, Viral Pneumonia, and Lung Opacity.

Segmentation of CT-Scan Images Using UNet Network for Patients Diagnosed with COVID-19 - Bernardo Gois, Francisco Nauber; Lobo Marques, Joao Alexandre (Computerized Systems for Diagnosis and Treatment of COVID-19, 2023)
The use of computational tools for medical image processing are promising tools to effectively detect COVID-19 as an alternative to expensive and time-consuming RT-PCR tests. For this specific task, CXR (Chest X-Ray) and CCT (Chest CT Scans) are the most common examinations to support diagnosis through radiology analysis. With these images, it is possible to support diagnosis and determine the disease’s severity stage. Computerized COVID-19 quantification and evaluation require an efficient segmentation process. Essential tasks for automatic segmentation tools are precisely identifying the lungs, lobes, bronchopulmonary segments, and infected regions or lesions. Segmented areas can provide handcrafted or self-learned diagnostic criteria for various applications. This Chapter presents different techniques applied for Chest CT Scans segmentation, considering the state of the art of UNet networks to segment COVID-19 CT scans and a segmentation experiment for network evaluation. Along 200 epochs, a dice coefficient of 0.83 was obtained.

Predictive models to the COVID-19 - Bernardo Gois, Francisco Nauber; Lima, Alex; Santos, Khennedy; Oliveira, Ramses; Santiago, Valdir; Melo, Saulo; Costa, Rafael; Oliveira, Marcelo; Henrique, Francisco das Chagas Douglas Marques; Neto, José Xavier; Martins Rodrigues Sobrinho, Carlos Roberto; Lôbo Marques, João Alexandre (Data Science for COVID-19, 2021)
Following the World Health Organization proclaims a pandemic due to a disease that originated in China and advances rapidly across the globe, studies to predict the behavior of epidemics have become increasingly popular, mainly related to COVID-19. The critical point of these studies is to discuss the disease's behavior and the progression of the virus's natural course. However, the prediction of the actual number of infected people has proved to be a difficult task, due to a wide range of factors, such as mass testing, social isolation, underreporting of cases, among others. Therefore, the objective of this work is to understand the behavior of COVID-19 in the state of Ceará to forecast the total number of infected people and to aid in government decisions to control the outbreak of the virus and minimize social impacts and economics caused by the pandemic. So, to understand the behavior of COVID-19, this work discusses some forecast techniques using machine learning, logistic regression, filters, and epidemiologic models. Also, this work brings a new approach to the problem, bringing together data from Ceará with those from China, generating a hybrid dataset, and providing promising results. Finally, this work still compares the different approaches and techniques presented, opening opportunities for future discussions on the topic. The study obtains predictions with R2 score of 0.99 to short-term predictions and 0.93 to long-term predictions.
Keywords: COVID-19; Forecast; Holt Winters; Kalman filter; Machine learning; Prophet; SEIR

LatinX in AI research - Banda, Juan M.; Ruiz-Garcia, Ariel; Montoya, Laura N.; Arraut, Ivan (Neural Computing and Applications, 2023)
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.

Machine learning over the free-parameters of the Black-Scholes equation: Stock market and Option market - Arraut, Jorge Mario; Arraut, Ivan; Lei, Ka I. (2023)
The Black-Scholes equation is famous for predicting values for the prices of Options inside the stock market scenario. However, it has the limitation of depending on the estimated value for the volatility. On the other hand, several Machine learning techniques have been employed for predicting the values of the same quantity. In this paper we analyze some fundamental properties of the Black-Scholes equation and we then propose a way to train its free-parameters, the volatility in particular. This with the purpose of using this parameter as the fundamental one to be learned by a Machine Learning system and then improve the predictions in the stock market.

The Hawking Radiation in Massive Gravity: Path Integral and the Bogoliubov Method - Arraut, Ivan; Segovia, Carlos; Rosado, Wilson (Universe, 2023)
We prove the consistency of the different approaches for deriving the black hole radiation for the spherically symmetric case inside the theory of Massive Gravity. By comparing the results obtained by using the Bogoliubov transformations with those obtained by using the Path Integral formulation, we find that in both cases, the presence of the extra-degrees of freedom creates the effect of extra-particles creation due to the distortions on the definitions of time defined by the different observers at large scales. This, however, does not mean extra-particle creation at the horizon level. Instead, the apparent additional particles perceived at large scales emerge from how distant observers define their time coordinate, which is distorted due to the existence of extra-degrees of freedom.
Number: 5 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Bogoliubov transformation method; Hawking radiation; Massive Gravity; Path Integral method; extra-degrees of freedom

Revenue Management in Airlines and External Factors Affecting Decisions: The Harmonic Oscillator Model - Arraut, Ivan; Rosado, Wilson; Leong, Victor (Mathematics, 2024)
The Revenue Management (RM) problem in airlines for a fixed capacity, single resource and two classes has been solved before by using a standard formalism. In this paper we propose a model for RM by using the semi-classical approach of the Quantum Harmonic Oscillator. We then extend the model to include external factors affecting the people’s decisions, particularly those where collective decisions emerge.
Number: 6 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: collective decisions; harmonic oscillator; revenue management; spontaneous symmetry breaking

A Quantum Field Formulation for a Pandemic Propagation - Arraut, Ivan; Marques, João Alexandre Lobo; Fong, Simon James; Li, Gloria; Gois, Francisco Nauber Bernardo; Neto, José Xavier (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
In this chapter, a mathematical model explaining generically the propagation of a pandemic is proposed, helping in this way to identify the fundamental parameters related to the outbreak in general. Three free parameters for the pandemic are identified, which can be finally reduced to only two independent parameters. The model is inspired in the concept of spontaneous symmetry breaking, used normally in quantum field theory, and it provides the possibility of analyzing the complex data of the pandemic in a compact way. Data from 12 different countries are considered and the results presented. The application of nonlinear quantum physics equations to model epidemiologic time series is an innovative and promising approach.
Keywords: COVID-19; Mathematical modeling; Nonlinear analysis; Quantum field theory

The Probability Flow in the Stock Market and Spontaneous Symmetry Breaking in Quantum Finance - Arraut, Ivan; Lobo Marques, João Alexandre; Gomes, Sergio (Mathematics, 2021)
The spontaneous symmetry breaking phenomena applied to Quantum Finance considers that the martingale state in the stock market corresponds to a ground (vacuum) state if we express the financial equations in the Hamiltonian form. The original analysis for this phenomena completely ignores the kinetic terms in the neighborhood of the minimal of the potential terms. This is correct in most of the cases. However, when we deal with the martingale condition, it comes out that the kinetic terms can also behave as potential terms and then reproduce a shift on the effective location of the vacuum (martingale). In this paper, we analyze the effective symmetry breaking patterns and the connected vacuum degeneracy for these special circumstances. Within the same scenario, we analyze the connection between the flow of information and the multiplicity of martingale states, providing in this way powerful tools for analyzing the dynamic of the stock markets.
Number: 21 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Hermiticity; conservation of the information; degenerate vacuum; flow of information; martingale condition; random fluctuations; spontaneous symmetry breaking; vacuum condition

The Role of the Volatility in the Option Market - Arraut, Ivan; Lei, Ka-I. (AppliedMath, 2023)
We review some general aspects about the Black–Scholes equation, which is used for predicting the fair price of an option inside the stock market. Our analysis includes the symmetry properties of the equation and its solutions. We use the Hamiltonian formulation for this purpose. Taking into account that the volatility inside the Black–Scholes equation is a parameter, we then introduce the Merton–Garman equation, where the volatility is stochastic, and then it can be perceived as a field. We then show how the Black–Scholes equation and the Merton–Garman one are locally equivalent by imposing a gauge symmetry under changes in the prices over the Black–Scholes equation. This demonstrates that the stochastic volatility emerges naturally from symmetry arguments. Finally, we analyze the role of the volatility on the decisions taken by the holders of the options when they use the solution of the Black–Scholes equation as a tool for making investment decisions.
Number: 4 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Black–Scholes equation; Merton–Garman equation; decision theory; option price; stock market; volatility

On the probability flow in the Stock market I: The Black-Scholes case - Arraut, Ivan; Au, Alan; Tse, Alan Ching-biu; Marques, Joao Alexandre Lobo (arXiv.org, 2020)
It is known that the probability is not a conserved quantity in the stock market, given the fact that it corresponds to an open system. In this paper we analyze the flow of probability in this system by expressing the ideal Black-Scholes equation in the Hamiltonian form. We then analyze how the non-conservation of probability affects the stability of the prices of the Stocks. Finally, we find the conditions under which the probability might be conserved in the market, challenging in this way the non-Hermitian nature of the Black-Scholes Hamiltonian.
Place: Ithaca, United States Publisher: Cornell University Library, arXiv.org Section: Quantitative Finance University: Cornell University Library arXiv.org
Keywords: General Finance

Gauge symmetries and the Higgs mechanism in Quantum Finance - Arraut, Ivan (arXiv, 2023)
By using the Hamiltonian formulation, we demonstrate that the Merton-Garman equation emerges naturally from the Black-Scholes equation after imposing invariance (symmetry) under local (gauge) transformations over changes in the stock price. This is the case because imposing gauge symmetry implies the appearance of an additional field, which corresponds to the stochastic volatility. The gauge symmetry then imposes some constraints over the free-parameters of the Merton-Garman Hamiltonian. Finally, we analyze how the stochastic volatility gets massive dynamically via Higgs mechanism.
arXiv:2306.03237 [q-fin]
Keywords: Quantitative Finance - General Finance

Gauge symmetries and the Higgs mechanism in Quantum Finance - Arraut, Ivan (Europhysics Letters, 2023)
By using the Hamiltonian formulation, we demonstrate that the Merton-Garman equation emerges naturally from the Black-Scholes equation after imposing invariance (symmetry) under local (gauge) transformations over changes in the stock price. This is the case because imposing gauge symmetry implies the appearance of an additional field, which corresponds to the stochastic volatility. The gauge symmetry then imposes some constraints over the free parameters of the Merton-Garman Hamiltonian. Finally, we analyze how the stochastic volatility gets massive dynamically via Higgs mechanism.
Publisher: EDP Sciences, IOP Publishing and Società Italiana di Fisica

Hawking Radiation as a Manifestation of Spontaneous Symmetry Breaking - Arraut, Ivan (Symmetry, 2024)
We demonstrate that black hole evaporation can be modeled as a process where one symmetry of the system is spontaneously broken continuously. We then identify three free parameters of the system. The sign of one of the free parameters governs whether the particles emitted by the black hole are fermions or bosons. The present model explains why the black hole evaporation process is so universal. Interestingly, this universality emerges naturally inside certain modifications of gravity.
Number: 5 Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Hawking radiation; black holes; spontaneous symmetry breaking

The solution to the Hardy's paradox - Arraut, Ivan (arXiv, 2023)
By using both, the weak-value formulation as well as the standard probabilistic approach, we analyze the Hardy's experiment introducing a complex and dimensionless parameter ($\epsilon$) which eliminates the assumption of complete annihilation when both, the electron and the positron departing from a common origin, cross the intersection point $P$. We then find that the paradox does not exist for all the possible values taken by the parameter. The apparent paradox only appears when $\epsilon=1$; however, even in this case we can interpret this result as a natural consequence of the fact that the particles can cross the point $P$, but at different times due to a natural consequence of the energy-time uncertainty principle.
arXiv:2106.06397 [physics]
Keywords: Physics - General Physics

The Tully-Fisher law and dark matter effects derived via modified symmetries - Arraut, Ivan (Europhysics Letters, 2023)
In any physical system, when we move from short to large scales, new spacetime symmetries emerge which help us to simplify the dynamics of the system. In this letter we demonstrate that certain variations on the symmetries of general relativity at large scales generate the effects equivalent to dark matter ones. In particular, we reproduce the Tully-Fisher law, consistent with the predictions proposed by MOND. Additionally, we demonstrate that the dark matter effects derived in this way are consistent with the predictions suggested by MOND, without modifying gravity.
Publisher: EDP Sciences, IOP Publishing and Società Italiana di Fisica

Influência da nova estrutura fiscal de impostos de Angola na gestão de escolas privadas do municipio do Lobito - Armando Carlos Hombo Nogueira; Luis Miguel Pacheco; Marcus Antonio Almeida Rodrigues (Revista Gestao em Analise, 2019)
0 citations (Crossref) [2022-09-21]

Analysis of Business Clusters in Macau - Alves, Jose; Trimarchi, Michael (University of Saint Joseph, 2016)

Macau's Strategies to Develop Training of Talented People with Expertise in the Cooperation between China and Portuguese Speaking Countries - Alves, Jose (University of Saint Joseph, 2015)

Airlines Perceptions of Airport Services - Alves, J (University of Saint Joseph, 2017)

Modelling the Neuromarketing application framework for tourism and entertainment industries in Macau and the Greater Bay Area (University of Saint Joseph, 2019)