The Introduction of Smallpox Vaccinations in the Pearl River Delta Region - Morais, Isabel (200th Anniversary of Smallpox Vaccines in the Pearl River Delta. Volume 1, 2007)

Dos Santos Albasini, João (1876–1922) - Morais, Isabel (The International Encyclopedia of Revolution and Protest, 2009)
Born in Magule, Mozambique (Portuguese East Africa), João dos Santos Albasini was a mulatto, the leading intellectual in the main center, Lourenço Marques (today, Maputo), the editor of O Africano (The African) founded 1908, and O Brado Africano (The African Voice) founded in 1918, and a champion of worker and African rights. Often characterized as a republican and a moderate, Albasini had a basic education and an appetite for ideas. He was an avid reader of republican theory, syndicalism, and anarchism – all influential in Portugal – and was familiar with a range of radical ideas circulating in the city's thriving café culture.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781405198073.wbierp0473
Keywords: 1800-1899; 1900-1999; Africa; Southern Africa; bibliography; colonialism; comparative history; imperialism; political history

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)

“Little Black Rose” at the 1934 Exposição Colonial Portuguesa - Morais, Isabel (Gendering the Fairs: Histories of Women and Gender at Fairs, 2010)
Publisher: University of Illinois Press Urbana, IL

The Inquisition in Goa and Macao in the 16th Century ; The Untold Story of Leonor da Fonseca, A Macanese New Christian (1593-1595) - Morais, Isabel (澳门学引论, 2010)

Panos, traje e moda em Angola: a linguagem política do corpo - Correia, Ana; Ribeiro, Xénia (Lusofonia, Encruzilhadas Culturais, Actas da Conferência sobre Lusofonia, 2011)

Hormones and Sexual Behavior of Teleost Fishes - Gonçalves, David; Oliveira, Rui F. (Hormones and Reproduction of Vertebrates, 2011)

Binding Ties of Miscegenation and Identity: The Narratives of Henrique Senna Fernandes (Macao) and Rex Shelley (Singapore) - Morais, Isabel Maria Da Costa (Portuguese and Luso-Asian Legacies in Southeast Asia, 1511–2011, vol. 1: The Making of the Luso-Asian World: Intricacies of Engagement, 2011)
Vários “pequenos” portugueses fizeram sentir a sua presença na “imensa Asia”, uns quase como reis, alguns como escravos, o maior número simplesmente como portugueses capazes de amar mulheres orientais e ser por elas amados. Capazes de fecundar mulheres de cor e fazer sair dos seus ventres portugueses também de cor.(Several “small” Portuguese made felt their presence in the “enormous Asia”, some as almost kings, others as slaves, the great majority just as Portuguese [who were] able to love oriental women and be loved by them. [They were] able to inseminate women of colour and to make their wombs produce other Portuguese also of colour.)Gilberto Freyre, Aventura e RotinaDespite the dynamics of globalization and rapid economic and political development, it is still noticeable nowadays that several Portuguese creolized communities in postcolonial societies have resisted cultural homogenization, particularly those scattered throughout the detached, peripheral regions of East and Southeast Asia that were under the Estado da Índia's sovereignty and influence (Goa, Daman, Diu, Sri Lanka, Malacca, Macao and Timor) and that the Portuguese created alongside the local political authorities (Indonesia and today's Singapore).By the beginning of the seventeenth century, the official population in the colonies of several territories in Asia that proudly claimed Portuguese ancestry had reached nearly one-and-a-half million individuals, as a legacy of colonial (dis)encounters. Centuries later, the Portuguese descendants of this “shadow empire” forged through trading, matrimonial alliances and cultural networks — notwithstanding a pragmatic adaptation to times of unprecedented political, economic and cultural upheaval — persist in a quest for identity and cultural reaffirmation of “Portuguese” cultural differentiation, which continues to be faithfully perpetuated and transmitted, centuries after the earlier Portuguese contacts ceased. These communities show distinctive aspects of what could be called a certain “Luso-Eurasianness”, exhibited in oral literature, religious practices, family surnames, ceremonies, cuisine, public structures, ways of speaking and, above all, in identity-making religious and cultural reinterpretation of lived and shared commonalities.This study argues that, even if relatively scant attention has been paid to the literary production of the communities considered here, in particular in Anglophone postcolonial studies, they have influenced and continue to exercise seminal influence on most postcolonial imaginaries, either in their respective societies or in the contemporary fiction of the Luso diaspora.

Law on Race and Slavery, Brazil, 1824 -1888 - Morais, Isabel (Encyclopedia of Free Blacks and People of Color in the Americas: The African-American Heritage of Freedom, 2011)
When Columbus arrived in 1492, the first free black person–a sailor–set foot in the Americas. Over the next 400 years, as slavery spread and became entrenched in the Western Hemisphere, free blacks built communities throughout North and South America, playing a critical role in every region, colony, and country. From Canada to the Caribbean to Chile, they established vital economic and social institutions, championed the cause of abolition, and formed a bridge between the worlds of free whites and enslaved blacks. They worked as artisans, farmers, ministers, merchants, shipbuilders, and reporters. Many free blacks served in the military and fought in every major war, including the American Revolution, the Haitian Revolution, and the Latin American wars for independence. Others served in government, and some–like presidents Bernardino Rivadavia of Argentina and Vicente Guerrero of Mexico–became national leaders.Free people of color in the United States and the Americas hold a unique status in global history. Never before and never since has such a group existed in large numbers anywhere in the world. Long shrouded in obscurity and overshadowed by scholarship on slavery and race, the free black community has become a growing and vibrant field of study as historians uncover vast material on this group, revealing how they lived, how they shaped society, and how they transformed the history of every nation in the hemisphere.Encyclopedia of Free Blacks and People of Color in the Americas is the first reference book to cover this crucial subject. Arranged alphabetically, this new, two-volume encyclopedia includes articles on all major events, issues, and concepts relevant to the free black community in the United States from the colonial period to the Civil War and in the rest of the Western Hemisphere from the late 1400s to the late 1800s, when emancipation became universal. Nearly 400 articles cover every country, colony, state, city, and region in the Americas with a significant presence of free blacks, and biographies, thematic articles, and entries on related subjects shed light on this fascinating topic. Featuring primary sources, illustrations, maps, tables, charts, a chronology, cross-references, suggestions for further reading, and a bibliography, this unique, original, and groundbreaking encyclopedia provides a wealth of information not available anywhere else.Entries include:-Abolitionist movement in Brazil -Zabeau Bellanton -Captain Cudjoe -Coffee cultivation -Education and literacy -Forten family -Free black artisans -French Caribbean -Gender attitudes -Guerrero (slave ship) -Haitian Revolution -La Escalera Plot -Laws of free birth -Legal discrimination on the basis of race -Living "as free" -Toussaint Louverture -Maroons -Marriage between free and slave -Midwives and traditional healers -Negro Convention Movement -Rebecca Protten -Somerset v. Stewart.

Francisca Diniz - Morais, Isabel (Feminist Writings from Ancient Times to the Modern World: A Global Sourcebook and History [2 volumes], 2011)
Collecting more than 200 sources in the global history of feminism, this anthology supplies an insightful record of the resistance to patriarchy throughout human history and around the world.From writings by Enheduana in ancient Mesopotamia (2350 BCE) to the present-day manifesto of the Association of Women for Action and Research in Singapore, Feminist Writings from Ancient Times to the Modern World: A Global Sourcebook and History excerpts more than 200 feminist primary source documents from Africa to the Americas to Australia.Serving to depict "feminism" as much broader—and older—than simply the modern struggle for political rights and equality, this two-volume work provides a more comprehensive and varied record of women's resistance cross-culturally and throughout history. The author's goal is to showcase a wide range of writers, thinkers, and organizations in order to document how resistance to patriarchy has been at the center of social, political, and intellectual history since the infancy of human civilization. This work addresses feminist ideas expressed privately through poetry, letters, and autobiographies, as well as the public and political aspects of women's rights movements.More than 200 chronologically arranged entries on feminist writers, thinkers, and organizations across 4,000 years of human historyContributions from more than 100 international scholars, including historians, sociologists, literary, cultural theorists, religious scholars, writers, and activistsBrief bibliographies of further readings, websites, and other relevant resources with each entryLists of entries arranged by region as well as by broad topic, in addition to a comprehensive index
Keywords: Social Science / Ethnic Studies / General; Social Science / Feminism & Feminist Theory

Henrietta Hall Shuck: Engendering Faith, Education, and Culture in Nineteenth-century Macao - Morais, Isabel (Americans and Macao: Trade, Smuggling, and Diplomacy on the South China Coast, 2012)
Chapter 7 Henrietta Hall Shuck Engendering Faith, Education, and Culture in Nineteenth-Century Macao Isabel Morais Introduction Henrietta Hall Shuck (1817–1844) is famous for being the first American female missionary in China. Despite her short period of residence in Macao in the early nineteenth century, her multiple experiences in the Portuguese colony are invaluable. Her pronouncements in her journal entries, correspondences and other writings make clear her perceptions of Christian interaction with the Chinese people. Her writings combine strong religious beliefs with an equally powerful commitment to promote gender equality through education . Excerpts from her journal openly address female child slavery, the mui tsai system (little girls sold as household servants and for prostitution), gender-based class hierarchies, and the exploitation of women and children. Henrietta helped establish the first Chinese girls’ school in Macao and promoted other important factors through her writing such as the “Camões’s Garden and Grotto” and her discussion of The Lusiad. Had Henrietta Hall not come to China, I might not be here today.1 The first four decades of the nineteenth century were critical years in the Pearl River Delta and Macao. Many examples show Chinese tightening political control over Macao and increased opposition to British incursions.2 In Portugal, several reforms aimed at reinforcing state control of the administrative, political, military, and economic colonial organizations were implemented and extended to Macao.3 In 1835, the governor of Macao ordered that Portuguese who were born in Macao or who had lived in Macao for a long time, be 106 Isabel Morais restricted to municipal affairs only and thereby reducing the political autonomy of the local elites.4 Meanwhile, other important legislation was also extended to Macao. A law passed in 1834 called for the dissolution of all religious orders and congregations, and the abolition of slavery in every Portuguese territory in 1836. These initiatives weakened the Catholic Church’s role in the education system since all schools for both Portuguese and Asian converts in Macao were church-affiliated under the Portuguese Padroado (Patronage) system in Asia.5 At the same time, the United States’ maritime expansion and foreign policy in Asia started to assume a more assertive role, promoting American social, political, and liberal ideas. In 1803, the governor of Macao prohibited the consul of the United States from spending the winter in Macao, forcing him to go to Canton.6 Driven by profits from trade, Americans were nonetheless encouraged to continue going to China, and despite restrictions in Macao, they used the city as a base for not only commerce but the promotion of religion as well. This was done despite the opposition of the British East India Company to missionary activity, the Chinese government’s prohibitions of publicly propagating religion and the local Catholic elite’s aversions to non-Catholics in the Portuguese colony.7 According to Reverend John Lewis Shuck, Henrietta’s husband, the Protestant missionaries in Macao were “strictly prohibited by the civil authority any public efforts for the diffusion of the gospel” being limited to personal conversations only.8 The persecution against Protestants in Portugal might have contributed to the intolerance among Roman Catholics in Macao. It is worth mentioning that between 1843 and 1846 around one thousand Jews fled from Portugal to the United States and West Indies (British island of Trinidad). In 1846 more than four hundred Jewish people fled from the Portuguese archipelago of Madeira to Jacksonville and Springfield, in the state of Illinois.9 On the other hand, the immigration of Catholics into the United States, resulted in the so-called “nativist” movement in the 1840s, and the rise of the anti-immigrant Know-Nothing Party of the 1850s.10 For many years Protestant missionaries in China were restricted to Guangzhou (Canton) and Macao. They concentrated on distributing literature among members of the foreign and Chinese merchant class, which gained a few converts. And they laid the foundations for more humanitarian efforts of advancing education in China among the lower classes and providing medical services to the needy. This situation would change after the Opium Wars led to Henrietta Hall Shuck 107 the imposition of treaties, and compelled the Chinese government to allow evangelization and freedom to convert Chinese to Christianity. In the 1830s, North American and British missionaries established bases in Macao to advance their evangelical operations. Amidst the restrictions and constraints of the diplomacy of the Canton system (ca. 1700–1842), which included a ban on foreign women entering China...

Jan Jacob Slauerhoff’s the forbidden realm: in Camoes’s footsteps from Lisbon to Macau - Morais, Isabel (The City and the Ocean: Journeys, Memory, Imagination, 2012)
Publisher: Cambridge Scholars Publishing

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

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

Darwinism, Freemasonry and print culture: The construction of identity of the Macanese colonial elites in the late nineteenth century - Morais, Isabel (Macao - The Formation of a Global City, 2013)
In his most quoted study Imagined Communities, Benedict Anderson argues that the invention of the printing press and the rise of print media contributed to a textual representation of the concept of the nation and nationalism. He states that ‘popular’ print culture was also crucial in its contribution to a global exchange that would have reinforced the idea of an ‘imagined community’.1 Anderson further explains that before the eighteenth century, the concept of nation was extensive, as Latin was the language of a broad, vast, imagined community called ‘Christendom’, but as there were changes in the religious communities, such a concept began to be replaced by French and English as vernacular languages of administrative centralization.2 Thus, print capitalism allied to the book market supported by the improvement of communications and the emergence of new and diverse forms of national languages, originated the creation of clusters of small creole ‘imagined political communities’ that were eager to promote new forms of national and cultural consciousness, aimed at widespread literacy through liens of kinship, ethnicity, fraternity, and power loyalties.3 This chapter posits that Anderson's arguments regarding creole nationalism in the new world, fit the particular case of the emergence of the printing, publishing and book-selling culture among a Euro-creole bourgeoisie from Macao with solid kinship, ethnic, commercial and social connections in Hong Kong, Canton, Shanghai and other littoral spaces in the treaty ports in East Asia, and takes these developments as a necessary point of departure. I argue that they used the widespread nature of print media to empower themselves and other community members with the progressive eighteenth-century Enlightenment ideas on rational scientific knowledge. They embraced atheism and anti-clericalism as important elements of enlightenment, thus promoting scientific culture, constitutional monarchy or republican forms of government, social mobility for ethnic minorities, and religious and intellectual tolerance that to a certain extent challenged the Catholic Church and conservative circles.
Num Pages: 19

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

Enhancing Educational Collaborations between China and SIngapore - Saw, Swee-Hock; Ge, Yun (Advancing Singapore-China Economic Relations, 2014)

Fish Sounds and Mate Choice - Amorim, M. Clara P.; Vasconcelos, Raquel O.; Fonseca, Paulo J. (Sound Communication in Fishes, 2015)
Fish acoustic signals associated with mating behaviour are typically low-frequency sounds produced by males when in close proximity to females. However, some species make sounds that serve the function and follow the design of advertisement calls, well known in insects, anurans, and birds. Close-range courtship acoustic signals may be used by females in mate assessment as they contain information of male quality such as size and condition. For example, sound-dominant frequency, amplitude, and fatigue resistance may signal body size whereas pulse period (i.e. muscle contraction rate) and calling activity are related with body condition in some species. Some signal features, such as sound pulse number, may carry multiple messages including size and condition. Playback experiments on mate choice of a restricted number of species suggest that females prefer vocal to silent males and may use sound frequency, amplitude, and mainly calling rateCalling ratewhen assessing males. The assessment of males by females becomes more challenging when males engage in choruses or when sounds are otherwise masked by anthropogenic noise but almost nothing is known about how these aspects affect mating decisions and fish reproductive success.
Keywords: Acoustic communication; Anthropogenic noise; Calling activity; Chorus; Fish; Mate choice; Reproductive success

The Post-Colonial Imaginary & Politics of Representation in the Macao SAR: The TEATRAU (Theatre showcase from Portuguese-speaking countries) & the (Re) emergence of 'Lusofonia' under Chinese stars - Morais, Isabel (Theatre 15 China, India & the Eastern World, 2016)

Catholic social teaching and environmental responsibility - Rothlin, Stephan; McCann, Dennis (A planetary and global ethics for climate change and sustainable energy, 2016)

Development of Structure and Sensitivity of the Fish Inner Ear - Vasconcelos, Raquel O.; Alderks, Peter W.; Sisneros, Joseph A. (Fish Hearing and Bioacoustics: An Anthology in Honor of Arthur N. Popper and Richard R. Fay, 2016)
Fish represent the largest group of vertebrates and display the greatest diversity of auditory structures. However, studies addressing how the form and function of the auditory system change during development to enhance perception of the acoustic environment are rather sparse in this taxon compared to other vertebrate groups. An ontogenetic perspective of the auditory system in fishes provides a readily testable framework for understanding structure–function relationships. Additionally, studying ancestral models such as fish can convey valuable comparable information across vertebrates, as early developmental events are often evolutionary conserved. This chapter reviews the literature on the morphological development of the fish auditory system, with particular focus on the inner ear structures that evolve from an otic placode during early embryonic development and then continue to undergo differentiation and maturation in the postembryonic phase. Moreover, the chapter provides a systematic overview of how auditory sensitivity develops during ontogeny. Although most studies indicate a developmental improvement in auditory sensitivity, there is considerably species-specific variation. Lastly, the paucity of information and literature concerning the development of auditory capabilities for social communication in fishes is also discussed. Further investigation on the development of structure and function of the fish auditory system is recommended in order to obtain a deeper understanding of how ontogenetic morphological changes in the auditory pathway relate to modifications in acoustic reception, auditory processing, and the capacity to communicate acoustically.
Keywords: Auditory development; Auditory physiology; Ear morphology; Fish ontogeny

Poesia e navegação: o impacto da história e do mito na definição de uma poética especificamente portuguesa - Borges, Vera (De Portugal a Macau. Filosofia e literatura no diálogo das culturas, 2017)
Maria Celeste Natário, Renato Epifânio, Carlos Ascenso André, Gonçalo Cordeiro, Inocência Mata, Jorge Rangel, Maria Antónia Espadinha

Macau Shaped by Use - Vernacular Customization of the City - Choi, Helen Hejung; Pai, Hyungmin (Imminent Commons: Commoning Cities", Seoul Biennale of Srchitecture and Urbanism, 2017)

Descobrimentos marítimos: miscigenação e preconceito em Senna Fernandes - Conde, Margarida (De Portugal a Macau. Filosofia e literatura no diálogo das culturas, 2017)

Abfaelle sind kostbar!" Konsumethische Perspektiven in Papst Franziskus' Enzyklika Laudaut Si - Gassner, Franz (Eine Wirtschaft, die Leben fördert wirtschafts- und unternehmensethische Reflexionen im Anschluss an Papst Franziskus, 2017)

Intra-Asia higher education mobilities - Ge, Yun; Ho, Kong Chong (Routledge Handbook of Asian Migrations, 2017)
Intra-Asian higher education mobility is a relatively new phenomenon in Asia and one triggered by the dynamic economic changes occurring in East Asia,
Publication Title: Routledge Handbook of Asian Migrations

Neuroendocrinology of Social Behavior in Teleost Fish - Gonçalves, David; Félix, Ana S.; Oliveira, Rui F. (Hormones, Brain and Behavior, 2017)

Charter UIA/UNESCO for Architectural Education - Mohamed, E.; Soares, Nuno; Revedin, J. (International Union of Architects, 2017)

International Business Ethics. What We Have Learnt by Focusing on China? - Rothlin, Stephan; McCann, Dennis (Eine Wirtschaft, die Leben fördert. Wirtschafts- und unternehmensethische Reflexionen im Anschluss an Papst Franziskus, 2017)

Macao Shaped by Use –Formalizing the Vernacular Customization of the City in Choi, H. & Pai, H. (ed.) - Soares, Nuno; F., Simões (Imminent commons: commoning cities, 2017)

Macao Shaped by Use –Formalizing the Vernacular Customization of the City in Choi - Soares, Nuno; Simões, F. (Imminent Commons: Commoning Cities: Seoul Biennale of Architecture and Urbanism, 2017)

Macao Shaped by Use – Formalizing the Vernacular Customization of the City - Soares, Nuno; Simões, Filipa (Imminent Commons: Commoning Cities: Seoul Biennale of Architecture and Urbanism 2017, 2017)

Beyong Mirrors: Research Pathways (CeiDE 2013-2017) (Attitudes and self-beliefs of ability towards mathematics and science and their effects on career choices: A case study with Macao-Chinese girls., 2018)

Education for justice-oriented and participatory citizenship in a politicized era in Hong Kong. (Handbook of Research on Education for Participative Citizenship and Global Prosperity, 2018)

Concordância verbal - Baxter, A. N.; Lopes, N. (Tânia Lobo (ed.) O português escrito por afro-brasileiros no século XIX: atas de reuniões da Sociedade Protetora dos Desvalidos, 2018)

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

Attitudes and self-beliefs of ability towards mathematics and science and their effects on career choices: A case study with Macao-Chinese girls - Correia, Ana; Fernandes, Clara; Maia, João (Beyong mirrors: Research pathways (CeiDE 2013-2017), 2018)

Inquérito aos estudantes da Universidade de São José: o peso da cultura na aprendizagem das línguas - Espadinha, M. A.; Borges, V. (A framework in Portuguese as a Foreign Language for Chinese Native Speakers, 2018)

Aesthetic experiences with young children in Hong Kong - Ho, C.K.L. (Meaning making in early childhood research: Pedagogies and the personal, 2018)

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

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

Creating multiculturalism amidst ethnic, linguistic and religious diversity: a Filipino perspective. - Monera, Arnold (Multiculturalism in Asia – Peace and Harmony, 2018)

Macau entre a ‘China Tropical’ e a Lusofonia a Oriente: Algumas achegas sobre os contextos colonial e pós-colonial - Morais, Isabel (Novas perspetivas sobre o luso-tropicalismo, Portuguese Studies Review PSR, 2018)

Portuguese as an Additional Language: Domains Use among Young Learners - Neves, Ana Cristina (Language Policy and Language Acquisition Planning, 2018)
Three key concepts will make up the pillars of this paper: second, foreign and heritage languages. Whenever appropriate “additional language” will be used as an umbrella term. A study of the domains of language use will be applied to these three different sociolinguistic contexts. To date, there are not many empirical studies on the domains of language and, more specifically, among young learners in different areal contexts, as it is the case of this study.
Keywords: Additional language; Domains of language use; Foreign language; Heritage language; Language policy; Second language

Investigating the urban rulesof the Pearl River Delta: a comparative approach to urban design research and teaching - Tieben, H.; Soares, Nuno; Yiu, E. (IN-TERSECTIONS. Expertise, AcademicResearch and Design from Barcelona, Beirut, Hong Kong, Brisbane, Auckland, Florence, 2018)

Potential for the design of an energy saving facade system using agglomerated cork: Implications in subtropical climates - Afonso, F. (Sustainable Buildings and Structures: Building a Sustainable Tomorrow, 2019)
Agglomerated cork is a known material by its contribution to the sustainment of the environment, not only because it is a wholly natural material, without chemical additives, but also because its industrial process of production results from the lowest quality residues of cork or industrial waste material, unsuitable for other applications. It is a reusable material, which means, the cork facade elements can be converted into a new agglomerated material, demonstrating a huge potential for adaptation to existing buildings following a reversible process. It is durable, lightweight, water resistant, low-cost material, some of the properties that may qualify it as suitable for application in large surfaces of vertical construction façades. The aim of this article is to analyze the mechanical, thermal and acoustic characteristics of cork composites against site-specific climatic conditions of subtropical climates and its suitability as an external coating system for residential buildings with the goal to reduce the energy consumption for cooling the inner environment. In high-density cities like Guangzhou, Shenzhen and Hong Kong the majority of the buildings starting from the 1960s until early 21st century (Brach & Song 2006), did not integrate thermal insulation systems into external walls, producing a high level of heat transfer through the external façade from the outside environment during spring and summer seasons. Due to the extremely fast urban growth of the modern Chinese city, little importance is given to the quality of the external walls in current residential building construction. For at least during six months each year the consumption of energy due to air conditioning in Guangdong province is extremely high. The study concluded that substantial energy could be saved by implementing an external coating upgrade to existing buildings. Additionally, this study details the result obtained through software for energy simulations (Design Builder, ENVI-met) demonstrating the potential of this project to produce homogeneous and comfortable inside temperatures, which cools the indoor ambient temperature in summer time.
Num Pages: 7

Principal perspectives - Correia, Ana; Tchiang, Van Man (Perspectives on Inclusion, 2019)

La Dottrina Sociale della Chiesa in Cina. Un riferimento per l’etica degli affari (“Catholic Social Teaching in China. A reference for Business Ethics”) - Rothlin, Stephan (La Chiesa in Cina. Un future da scrivere, 2019)

A Alma e o Lugar de uma Comunidade Singular - Simoes, José Manuel (O Macaense - Identidade, Cultura e Quotidiano, 2019)

Original Sin and Reprobation in Renaissance Thomism: The Cases of Domingo Bañez and John of St. Thomas - Cai, Thomas Yilun (Nos sumus tempora, 2020)

A figura feminina na ficção de Senna Fernandes: identidade, subalternidade e agência - Correia, Ana (O Macaense. Identidade e cultura e quotidiano, 2020)

Re-thinking Chinese Ecumene in the Global Age - Duraj, Jaroslaw (Eric Voegelin’s Asian Political Thought, 2020)
The rise of Asia in global affairs has forced western thinkers to rethink their assumptions, theories, and conclusions about the region. Eric Voegelin’s Asian Political Thought brings together a mixture of established and rising scholars from both Asia and the West to reflect upon the political philosopher’s thought about China, Japan, Korea, Central Asia, and India. From Voegelin’s writings, readers will not only understand how Voegelin’s approach can illuminate the fundamental principles and issues about Asia but also what are the challenges and possibilities that Asia offers in the twentieth-first century. For those who want to move past the superficial commentary and clichés about Asia, Eric Voegelin’s Asian Political Thought is the book for you.

Interculturality and formation - Gallares, Judette (Engaging our diversity : interculturality and consecrated life today, 2020)

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.

Ogień zapalony niegdyś na górze Moria: Woltyła i Newman o warunkach dla propozycju Chrystusa'=The fire once kindled on Moriah: Wojtyła and Newman on the conditions for the proposal of Christ - Morgan, Stephen (Jan Paweł II: Komunikacja i Kultura, 2020)

Resources for Future in a Caring Economy - Gassner, Franz (Menschenrechte und Gerechtigkeit als bleibende Aufgaben, 2020)

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)

Towards an Approach to the Interactive Filmic Narrative - Caires, Carlos Sena (Image in the post-millennium: mediation, process and critical tension, 2021)

Virtual Guia Fortress: A 3D-printed eXtended Reality Playset - Chau, Iok Fong; Cardoso, Jorge C. S.; Estadieu, Gerald (Entertainment Computing – ICEC 2021, 2021)
Series Title: Lecture Notes in Computer Science

The Metaxological Philosophy of Dialogue with Buddhism - Duraj, Jaroslaw (The Wheel & The Cross: An Anthology by Jesuits & Friends on Buddhism and Dialogue, 2021)

Zen-Ignatian Training Program in Japan: A Personal Experience - Duraj, Jaroslaw (The Wheel & The Cross: An Anthology by Jesuits & Friends on Buddhism and Dialogue, 2021)

Challenges and Learning Strategy for young children with special needs during the pandemic in Indonesia - Fridani, L.; Ikegami, Kiiko (Anthology Challenges in Management of Early Childhood Education during Pandemic, 2021)

Time, authenticity and photographic storytelling in The Museum of Innocence. - Hannam, Kevin; Ryan, Edward (Authenticity and authentication of heritage, 2021)
GSCC: 0000014

Translating Two Minds in the Tradition of One Faith: Considerations of Intercultural Dynamics in the parallels of John Henry Newman (1801-1890) and Joseph Ma Xiangbo (1840-1939) - Law, Cyril Jerome (Sacred and the Everyday: Comparative Approaches to Literature, Religious and Secular, 2021)
Interculturality is considered a constant given in the development of most major religious movements during the process of propagation coming into contact with diverse tongues, mores, and sentiments. And one of the chief, if not decisive, instruments contributing to this ever dynamic spread and reception of beliefs and cultures is translation. Christianity purports to be an incarnational religion, where the Word made flesh expresses the di-vine in human terms. Its doctrines are enshrined in a faith tradition that is developed largely through interpretation and translation. This short paper will cut into this sacral literary tradition by paralleling two influential mod-ern Christian thinkers, John Henry Newman from the Anglophone school, and Joseph Ma Xiangbo from the Orient, to see how attempts at translating the ideas and works of people from distinct cultural milieux is both reflec-tive of the necessary developmental nature of Christian teachings in the historical continuum of time and space, and indicative of the intellectual challenges that never cease to accompany the literary effervescence stem-ming from comparative religious studies.

What Goes Around Comes Around? The (Non-)Existence of (Divine) Retribution in Ancient Chinese Literature and the Hebrew Bible - Leong, Andrew Chin Hei (Sacred and the Everyday: Comparative Approaches to Literature, Religious and Secular, 2021)

Religious Epistemology in Analytic Theology - McNabb, Tyler Dalton; Baldwin, Erik (T&T Clark Handbook of Analytic Theology, 2021)
GSCC: 0000003

Liturgical Text as Mandorla: windows from the Everyday to the Sacred, from the Sacred to the Everyday - Morgan, Stephen (Sacred and the Everyday: Comparative Approaches to Literature, Religious and Secular, 2021)

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)

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

Soka Education Philosophy as a Foundation for Teacher Preparation in Creating Inclusive Education - Agbenyega, Joseph Seyram; Ikegami, Kiiko; Rivalland, Corine (International Perspectives on Inclusive Education, 2021)
Current global shifts in education towards inclusive early childhood education are deeply engineered by the crisis of educational exclusion. In responding to exclusion, teachers have mainly utilized dominant western theories to plan and implement inclusive teaching. In this chapter, we draw on a non-western philosophy, a Nichiren Buddhist (Soka) philosophy, to provide a ‘kaleidoscopic’ lens through which to create inclusive educational learning spaces that engender full participation of all children. The Soka education philosophy is a humanist concept which can guide teachers when preparing to create inclusive education. The aims of this chapter are threefold: The first is an exploration of the Nichiren Buddhist (Soka) philosophy. The second aim is to highlight how this philosophy can enable teachers to unleash the unlimited potential of children in inclusive learning settings. Thirdly, we argue that grounding early childhood teacher education in this philosophy can help improve the effectiveness of inclusive educational experience for all children.

Enhancing Teacher Education by Utilizing a Revised PGDE Curriculum as a Fundamental Resource for Inclusive Practices in Macao - Monteiro, Elisa; Forlin, Chris (International Perspectives on Inclusive Education, 2021)
Keywords: Inclusive education; Knowledge transfer; Pedagogical practice; Post-graduate diploma in education; Programme design; Teachers

Forming Intercultural Missionaries - Gallares, Judette (Becoming Intercultural: Perspectives on Mission, 2021)

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

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

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

Journalism Ethics and the Common Good: The Formation of Values and Virtues for Just and Harmonious Societies - Gassner, Franz; Simoes, José Manuel (Disentangled Vision On Higher Education: Preparing The Generation Next, 2022)

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

Breve Abordagem ao Percurso Vivencial e Poético de Um ‘Autor Maldito’: Carlos Augusto Montalto de Jesus (1863-1932) na China e pelo Mundo Fora - Morais, Isabel (Mapas Esquivos” no Centenário de Sophia de Mello Breyner Andresen (1919-2019): Navegação a Oriente, 2022)

The combat of truth and error: Newman and Chesterton on heresy - Morgan, Stephen (Lead Kindly Light. Essays for Ian Ker, 2022)

Traços transdisciplinares na obra do Padre Manuel Antunes: uma análise crítica à luz da Carta da Transdisciplinaridade /UNESCO-1994 - Mucheroni, M. L; Fernandes-Marcos, A (Repensar Portugal, a Europa e a Globalização – Saber Padre Manuel Antunes, SJ – 100 anos, 2022)
Toda a obra e pensamento do Padre Manuel Antunes se revestem de características de grande abrangência e de capacidade de abertura à inovação, na perspetiva de que o pensamento crítico, sendo perscrutador do desconhecido, enquanto questiona o conhecimento adquirido ou em pesquisa, não se pode fechar em si mesmo ou separar partes do conhecimento de um todo que constitui o universo, e o homem como parte deste, já que se objetiva a compreensão última do Todo. Encontramos, portanto, traços de transdisciplinaridade na obra e pensamento do Padre Manuel Antunes indicando um pioneirismo relativamente ao movimento da transdisciplinaridade que arranca com o primeiro congresso da área e a respetiva carta daí resultante. Neste artigo, os autores propõem uma análise crítica da obra do Padre Manuel Antunes à luz dos princípios fundacionais encontrados na Carta da Transdisciplinaridade de 1994.

How Schools in Macau Create Intellectual Capital for Development - Ng, Shun-wing; Kwan, Yee-wan (Managing School Intellectual Capital for Strategic Development, 2022)
This chapter describes how intellectual capital comprising human capital, structural capital, and relational capital are being created for school development and quality assurance in Macau. Macau has aimed to catch up with the global education reform by subsidising majorities of the non-tertiary sectors and promulgating Decree Laws regarding education policies and development. Despite the significance of the intangible assets of the intellectual capital, the chapter also attempts to analyse the issues and challenges towards the management of intellectual capital emerging simultaneously in the transition process in the educational context of Macau. It suggests capitalising on the accumulated school knowledge for school effectiveness. This chapter depicts the chronological development of Macau's education reform by analysing how Macau has attempted to emancipate its education institutions from the period of quasi-closed system to that of the open system by creating different types of intellectual capital in school. It discusses the emerging issues and challenges simultaneously in the transition process of educational development in Macau, namely before and after returning its sovereignty to the Chinese government.
Num Pages: 12

Macau: 7 desenhos, 7 artistas, 7 perfis, 7 pontes entre a China e o mundo lusófono - Simoes, José Manuel (Em português: falar, viver e pensar no século XXI, 2022)

Macau: Carlos Marreiros, macaense, luso-descendente – um testemunho de uma carreira internacional de um arquiteto e artista - Simoes, José Manuel (Em português: falar, viver e pensar no século XXI, 2022)

The Media in São Tomé and Príncipe and Its Contribution to the Country Development - Simoes, José Manuel (China, Guinea-Bissau, Mozambique and São Tomé and Príncipe – From sporadic bilateral exchanges to a comprehensive multilateral platform, 2022)

The pedagogical role of ethics and deontology for future professionals of communication and media: How to develop and nourish virtues - Simões, José Manuel (IV Jornadas Innovación Educativa en Comunicación y Alfabetización Mediática, 2022)
- Flipped classroom metodologiak eskaintzen dituen abantaila pedagogikoak (Ander Goikoetxea Pérez, Hannot Mintegia Beaskoa). - Conocimiento de la actualidad informativa a partir de la participación del alumnado que ejerce de periodista y lector crítico (María del Mar Rodríguez González, Iñigo Marauri Castillo, Guillermo Gurrutxaga Rekongo). - El papel del procesamiento dual de la información en la discriminación de noticias falsas (José Manuel Meza Cano, Cinthia Aranda-Solís, Blanca Olalde López de Arechavaleta, Santiago Palacios Navarro). - No trespassing: Arau, traba eta mugen bidezko metodologia sortzaile bat kazetaritza gradurako (Hannot Mintegia Beaskoa, Ander Goikoetxea Pérez). - Learning digital journalism: Analysing web media in comparative perspective to learn what is quality in digital communication (Javier Díaz-Noci). - El sistema híbrido vehículo de comunicación educativa (Antonio Vaquerizo Mariscal). - The pedagogical role of ethics and deontology for future professionals of communication and media: How to develop and nourish virtues (José Manuel Simões). - Desgaitasuna duten pertsonen Komunikazio ikasketetako prestakuntzari buruzko gogoetak (Terese Mendiguren, Jesús Ángel Pérez Dasilva, Koldobika Meso Ayerdi, Simón Peña, Ainara Larrondo, María Ganzabal). - Teaching Communication (and Journalism) History from Social History Theory: Some proposals (Javier Díaz-Noci).

Um país, dois sistemas: reflexões sobre o panorama mediático em língua portuguesa em Macau - Simoes, José Manuel (Em português: falar, viver e pensar no século XXI, 2022)

Mangroves as a nature-based solution for water and climate change issues in Macao: from scientific research to environmental education - Tagulao, Karen (Fostering applied research on the synergies between biodiversity and climate, 2022)
Publisher: Deutschland / Bundesamt für Naturschutz

Nature-Based Solutions for Environmental Education in the East Asian Context - Tagulao, Karen Araño (Enhancing Environmental Education Through Nature-Based Solutions, 2022)
Environmental education (EE) has long been practiced worldwide, while Nature-based solutions (NBS) is a relatively new concept. This chapter aims to provide an overview of the EE and NBS practices in East Asia and evaluate how these two valuable applications can be used concurrently. East Asia has a well developed environmental education (EE) programs and activities, both in formal and informal education. These ranges from developing green schools and campuses to establishing policies and acts. While EE has been actively practiced for decades in the region, the adoption of NBS to address environmental and societal challenges is limited. The educational benefits and opportunities from NBS are also lacking. Although there are some projects that can be classified as NBS, like the use of wetlands for wastewater treatment, they are not clearly categorized as one. These projects are also not integrated into environmental education programs. Considering this, the region should develop innovative environmental education programs for schools, universities and communities, that integrate NBS projects. Integrating the two together will boost the effectiveness of environmental education in raising environmental awareness and changing the environmental attitude and behavior of people, which will also help address societal issues.
Keywords: Environmental awareness; Environmental policies/acts; Green schools; Green universities; Sponge cities; Wetlands

Key Issues for Digital Factory Designing and Planning: A Survey - Wang, Han; Du, Wencai; Li, Shaobin (Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2022)
Digital Factory (DF) planning is the key of intelligent factory construction, where intelligent production technologies of big data analysis, cloud computing, blockchain, Internet of Things, artificial intelligence, 5G, Time Sensitive Network (TSN), Digital Twin (DT), additive manufacturing are included. By applying the modern techniques, DF performs great advantages on the aspects of product lifecycle management, enterprise resource planning, operation management, supply chain management, real-time database construction, advanced process control, as well as the new technologies of distributed control system and fieldbus control system. This article delivers a review of key issues of DF top-level design and planning from the aspects of networking, precision, automation and digitalization. Solutions are explored based on 5G, TSN and DT advanced technologies, literately and practically. Additionally, the article describes the method and application of efficient big data comprehensive solution. Therefore, this study contributes valuable decision-making support for DF applications.
Keywords: 5G; Big data comprehensive solution; Digital Factory; Digital twin; Time Sensitive Network

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

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

Tourist Sentiment Mining Based on Deep Learning - Li, Weijun; Yang, Qun; Du, Wencai (Artificial Intelligence, 2022)
Mining the sentiment of the user on the internet via the context plays a significant role in uncovering the human emotion and in determining the exactness of the underlying emotion in the context. An increasingly enormous number of user-generated content (UGC) in social media and online travel platforms lead to development of data-driven sentiment analysis (SA), and most extant SA in the domain of tourism is conducted using document-based SA (DBSA). However, DBSA cannot be used to examine what specific aspects need to be improved or disclose the unknown dimensions that affect the overall sentiment like aspect-based SA (ABSA). ABSA requires accurate identification of the aspects and sentiment orientation in the UGC. In this book chapter, we illustrate the contribution of data mining based on deep learning in sentiment and emotion detection.

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.

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.

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)

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

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.

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%.

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.

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.

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)

A DCRC Model for Text Classification - Hao, Zhaoquan; Jin, Jiangyong; Liang, Shengbin; Cheng, Suying; Shen, Yanqing (Computer and Information Science, 2023)
Traditional text classification models have some drawbacks, such as the inability of the model to focus on important parts of the text contextual information in text processing. To solve this problem, we fuse the long and short-term memory network BiGRU with a convolutional neural network to receive text sequence input to reduce the dimensionality of the input sequence and to reduce the loss of text features based on the length and context dependency of the input text sequence. Considering the extraction of important features of the text, we choose the long and short-term memory network BiLSTM to capture the main features of the text and thus reduce the loss of features. Finally, we propose a BiGRU-CNN-BiLSTM model (DCRC model) based on CNN, GRU and LSTM, which is trained and validated on the THUCNews and Toutiao News datasets. The model outperformed the traditional model in terms of accuracy, recall and F1 score after experimental comparison.
Keywords: BiGRU; BiLSTM; CNN; Text classification

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

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.

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.

‘Culture and identity – nationality and nationalism: indications for a theological reflection’ - Morgan, Stephen (Memory and Identity: the proceedings of the 28th ASEACCU Annual Conference, 2023)

To realize an everyday holiness”: Newman, imagination, and the virtue of religion - Morgan, Stephen (A Guide to the Life and Thought of John Henry Newman, 2023)

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.

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

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

Human Resource Management and Employee Relations in Angola: Challenges and Opportunities - Silva, Maria Rita (Employee Relations and Trade Unions in Africa: A Critical Approach, 2023)
This chapter presents a systematic review of research on human resources management (HRM) and employee relations (ER) in Angola to identify the main challenges and opportunities presented. To achieve that goal, this chapter characterises research conducted in the country, investigates its main findings, and proposes some directions for the future. Based on a bibliographic search in the EBSCO Discovery database of empirical articles about HRM and ER in Angola, we collected a sample of 28 studies published between 2009 and 2022. Most studies have focused on the development and retention of human resources. Other topics included diversity management, workplace attitudes and behaviours, scale validations, leadership and decision-making, performance appraisal, quality assessment, corporate social responsibility, and expatriates. We identified three main challenges and opportunities in HRM and ER in Angola. First, the policies and the planning, implementing, and evaluating processes of human resources development and retention strategies should be improved. Second, effective leadership and participation should be promoted while navigating the tensions between autocratic and participative leadership styles. Finally, positive ER and employee well-being should be promoted. Understanding these challenges and opportunities may contribute to the development of human capital in Angola and, ultimately, the country’s socioeconomic development.

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)

Hierarchical Medical Classification Based on DLCF - Yao, Mingyuan; Sun, Haoran; Liang, Shengbin; Shen, Yanqing; Yukie, Niki (Computer and Information Science, 2023)
Medical classification is affected by many factors, and the traditional medical classification is usually restricted by factors such as too long text, numerous categories and so on. In order to solve these problems, this paper uses word vector and word vector to mine the text deeply, considering the problem of scattered key features of medical text, introducing long-term and short-term memory network to effectively retain the features of historical information in long text sequence, and using the structure of CNN to extract local features of text, through attention mechanism to obtain key features, considering the problems of many diseases, by using hierarchical classification. To stratify the disease. Combined with the above ideas, a deep DLCF model suitable for long text and multi-classification is designed. This model has obvious advantages in CMDD and other datasets. Compared with the baseline models, this model is superior to the baseline model in accuracy, recall and other indicators.
Keywords: Dual channel; Hierarchical classification; LSTM-CNN; Medical classification; RF

Visuality and Infrastructure: The Case of the Belt and Road Initiative - Zuev, Dennis (The Palgrave Handbook of Globalization with Chinese Characteristics, 2023)

Design Thinking Methodology and Text-To-Image Artificial Intelligence: A Case Study in the Context of Furniture Design Education - Caires, Carlos Sena; Estadieu, Gerald; Olga Ng Ka Man, Sandra (Perspectives on Design and Digital Communication IV: Research, Innovations and Best Practices, 2024)
The design thinking methodology is a problem-solving approach that involves empathising with end-users, (re)defining problems, brainstorming solutions creatively, and experimenting with prototypes and testing. It has been widely adopted in education to help students develop critical thinking, creativity, and problem-solving skills in design. On the other hand, text-to-image artificial intelligence is a method used to generate images from natural language descriptors (usually referred to as prompts). Design thinking methodology can teach students to think creatively and critically about real-world problems when applied in the classroom. In the context of design teaching at the University of Saint Joseph, Macao, students use the design thinking methodology to develop innovative proposals for furniture design solutions. Combining design thinking methodologies with text-to-image artificial intelligence can further enhance the learning experience by allowing students to generate visual representations of their ideas during the ideation phase. The authors developed a systematic approach to generate images for ideation on furniture design based on prompting text-to-image (PTI). The analysis related students’ results who applied the design thinking methodology without using AI tools and the results generated using a standard text-to-image programme. By combining both methods, teachers can help students develop critical thinking, creativity, and problem-solving skills, while also allowing them to generate visual representations in a different paradigm and, by so, being able to communicate their ideas with the most appropriate support for them.
Keywords: Artificial intelligence; Design thinking; Education quality; Furniture design education; Text-to-image prompt

Integrating digital technologies during the COVID-19 kindergarten suspension period in Hong Kong. - Hu, X.; Yelland, N.; Leung, W. M. V.; Liang, Y.; Sun, C. R.; Graham, C. R. (Digital Technologies and Early Childhood in China: Policy and Practice, 2024)

Modelos de Incorporação do Desenvolvimento Sustentável nos Acordos de Comércio - Rafael, Ângelo Patrício (Uma viagem Jurídica Entre o Rio das Pérolas e a Pérola do Índico: Publicação Comemorativa dos 25 Anos da Cooperação entre a Faculdade de Direito da Universidade Eduardo Mondlane (FDUEM) e a Faculdade de Direito da Universidade de Macau (FDUM), 2024)

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

Once More with Feeling: The Debate Over Yalta Resurrected [Concluding Remarks] - Roberts, Priscilla (H-Diplo State of the Field Roundtable on the Eastern European Settlements during the Second World War: Making the Peace Amidst the War, 2024)