Education University of Hong Kong

Unsupervised learning with generative adversarial networks (GANs) has proven hugely successful. Regular GANs hypothesize the discriminator as a classifier with the sigmoid cross entropy loss function. However, we found that this loss function may lead to the vanishing gradients problem during the learning process. To overcome such a problem, we propose in this paper the Least Squares Generative Adversarial Networks (LSGANs) which adopt the least squares loss function for the discriminator. We show that minimizing the objective function of LSGAN yields minimizing the Pearson X2 divergence. There are two benefits of LSGANs over regular GANs. First, LSGANs are able to generate higher quality images than regular GANs. Second, LSGANs perform more stable during the learning process. We evaluate LSGANs on LSUN and CIFAR-10 datasets and the experimental results show that the images generated by LSGANs are of better quality than the ones generated by regular GANs. We also conduct two comparison experiments between LSGANs and regular GANs to illustrate the stability of LSGANs.

A new periodontitis classification scheme has been adopted, in which forms of the disease previously recognized as "chronic" or "aggressive" are now grouped under a single category ("periodontitis") and are further characterized based on a multi-dimensional staging and grading system. Staging is largely dependent upon the severity of disease at presentation as well as on the complexity of disease management, while grading provides supplemental information about biological features of the disease including a history-based analysis of the rate of periodontitis progression; assessment of the risk for further progression; analysis of possible poor outcomes of treatment; and assessment of the risk that the disease or its treatment may negatively affect the general health of the patient. Necrotizing periodontal diseases, whose characteristic clinical phenotype includes typical features (papilla necrosis, bleeding, and pain) and are associated with host immune response impairments, remain a distinct periodontitis category. Endodontic-periodontal lesions, defined by a pathological communication between the pulpal and periodontal tissues at a given tooth, occur in either an acute or a chronic form, and are classified according to signs and symptoms that have direct impact on their prognosis and treatment. Periodontal abscesses are defined as acute lesions characterized by localized accumulation of pus within the gingival wall of the periodontal pocket/sulcus, rapid tissue destruction and are associated with risk for systemic dissemination.

Food security is a high-priority issue for sustainable global development both quantitatively and qualitatively. In recent decades, adverse effects of unexpected contaminants on crop quality have threatened both food security and human health. Heavy metals and metalloids (e.g., Hg, As, Pb, Cd, and Cr) can disturb human metabolomics, contributing to morbidity and even mortality. Therefore, this review focuses on and describes heavy metal contamination in soil-food crop subsystems with respect to human health risks. It also explores the possible geographical pathways of heavy metals in such subsystems. In-depth discussion is further offered on physiological/molecular translocation mechanisms involved in the uptake of metallic contaminants inside food crops. Finally, management strategies are proposed to regain sustainability in soil-food subsystems.

An artificial intelligence-based chatbot, ChatGPT, was launched in November 2022 and is capable of generating cohesive and informative human-like responses to user input. This rapid review of the literature aims to enrich our understanding of ChatGPT’s capabilities across subject domains, how it can be used in education, and potential issues raised by researchers during the first three months of its release (i.e., December 2022 to February 2023). A search of the relevant databases and Google Scholar yielded 50 articles for content analysis (i.e., open coding, axial coding, and selective coding). The findings of this review suggest that ChatGPT’s performance varied across subject domains, ranging from outstanding (e.g., economics) and satisfactory (e.g., programming) to unsatisfactory (e.g., mathematics). Although ChatGPT has the potential to serve as an assistant for instructors (e.g., to generate course materials and provide suggestions) and a virtual tutor for students (e.g., to answer questions and facilitate collaboration), there were challenges associated with its use (e.g., generating incorrect or fake information and bypassing plagiarism detectors). Immediate action should be taken to update the assessment methods and institutional policies in schools and universities. Instructor training and student education are also essential to respond to the impact of ChatGPT on the educational environment.

The photocatalytic performance of the star photocatalyst g-C3N4 was restricted by the low efficiency because of the fast charge recombination. The present work developed a facile in situ method to construct g-C3N4/g-C3N4 metal-free isotype heterojunction with molecular composite precursors with the aim to greatly promote the charge separation. Considering the fact that g-C3N4 samples prepared from urea and thiourea separately have different band structure, the molecular composite precursors of urea and thiourea were treated simultaneously under the same thermal conditions, in situ creating a novel layered g-C3N4/g-C3N4 metal-free heterojunction (g-g CN heterojunction). This synthesis method is facile, economic, and environmentally benign using easily available earth-abundant green precursors. The confirmation of isotype g-g CN heterojunction was based on XRD, HRTEM, valence band XPS, ns-level PL, photocurrent, and EIS measurement. Upon visible-light irradiation, the photogenerated electrons transfer from g-C3N4 (thiourea) to g-C3N4 (urea) driven by the conduction band offset of 0.10 eV, whereas the photogenerated holes transfer from g-C3N4 (urea) to g-C3N4 (thiourea) driven by the valence band offset of 0.40 eV. The potential difference between the two g-C3N4 components in the heterojunction is the main driving force for efficient charge separation and transfer. For the removal of NO in air, the g-g CN heterojunction exhibited significantly enhanced visible light photocatalytic activity over g-C3N4 alone and physical mixture of g-C3N4 samples. The enhanced photocatalytic performance of g-g CN isotype heterojunction can be directly ascribed to efficient charge separation and transfer across the heterojunction interface as well as prolonged lifetime of charge carriers. This work demonstrated that rational design and construction of isotype heterojunction could open up a new avenue for the development of new efficient visible-light photocatalysts.

The extensive use of antibiotics leading to the rapid spread of antibiotic resistance poses high health risks to humans, but to date there is still lack of a quantitative model to properly assess the risks. Concerns over the health risk of antibiotic residues in the environment are mainly (1) the potential hazard of ingested antibiotic residues in the environment altering the human microbiome and promoting emergence and selection for bacteria resistance inhabiting the human body, and (2) the potential hazard of creating a selection pressure on environmental microbiome and leading to reservoirs of antibiotic resistance in the environment. We provide a holistic view of health risk assessment of antibiotic resistance associated with antibiotic residues in the environment in contrast with that of the antibiotic resistant bacteria and discuss the main knowledge gaps and the future research that should be prioritized to achieve the quantitative risk assessment. We examined and summarized the available data and information on the four core elements of antibiotic resistance associated with antibiotic residues in the environment: hazard identification, exposure assessment, dose-response assessment, and risk characterization. The data required to characterize the risks of antibiotic residues in the environment is severely limited. The main future research needs have been identified to enable better assessments of antibiotic resistance associated with antibiotic residues in the environment: (1) establishment of a standardized monitoring guide of antibiotic residues and antibiotic resistance in the environment, (2) derivation of the relationship between antibiotic levels and pathogenic antibiotic-resistance development in different settings, and (3) establishment of the dose-response relationship between pathogenic antibiotic resistant bacteria and various infection diseases. After identification of key risk determinant parameters, we propose a conceptual framework of human health risk assessments of antibiotic residues in the environment. CAPSULE: A holistic view of human health risk assessment of antibiotic residues in the environment was provided.

A new periodontitis classification scheme has been adopted, in which forms of the disease previously recognized as "chronic" or "aggressive" are now grouped under a single category ("periodontitis") and are further characterized based on a multi-dimensional staging and grading system. Staging is largely dependent upon the severity of disease at presentation as well as on the complexity of disease management, while grading provides supplemental information about biological features of the disease including a history-based analysis of the rate of periodontitis progression; assessment of the risk for further progression; analysis of possible poor outcomes of treatment; and assessment of the risk that the disease or its treatment may negatively affect the general health of the patient. Necrotizing periodontal diseases, whose characteristic clinical phenotype includes typical features (papilla necrosis, bleeding, and pain) and are associated with host immune response impairments, remain a distinct periodontitis category. Endodontic-periodontal lesions, defined by a pathological communication between the pulpal and periodontal tissues at a given tooth, occur in either an acute or a chronic form, and are classified according to signs and symptoms that have direct impact on their prognosis and treatment. Periodontal abscesses are defined as acute lesions characterized by localized accumulation of pus within the gingival wall of the periodontal pocket/sulcus, rapid tissue destruction and are associated with risk for systemic dissemination.

Microplastics are emerging contaminants and their presence in water and soil ecosystems has recently drawn considerable attention because they pose a great threat to entire ecosystems. Recent researches have focused on the detection, occurrence, characterization, and toxicology of microplastics in marine and freshwater ecosystems; however, our understanding of the ecological effects of microplastics in soil ecosystems is still limited compared with that in aquatic ecosystems. Here, we have compiled literature, studying the sources, migration of microplastics in soil, negative impacts on soil health and function, trophic transfer in food chains, and the corresponding adverse effects on soil organisms in order to address the potential ecological and human health risks caused by microplastics in soil. This review aims to address gaps in knowledge, shed light on the ecological effects of microplastics in soil, and propose future studies on microplastic pollution and the resultant soil ecotoxicity. Furthermore, this review is focused on limiting microplastics in soil and establishing management and remediation measures to mitigate the risks posed by microplastic pollution.

In this technology review, we explore the affordances of the generative AI chatbot ChatGPT for language teaching and learning. In addition to this, we also present debates and drawbacks of ChatGPT. Finally, we present the digital competencies teachers and learners require to use this chatbot ethically and effectively to support language learning.

Purpose This paper aims to present a research‐based model of leadership for learning. It argues that the field has made substantial progress over the past 40 years in identifying ways in which leadership contributes to learning and school improvement. Four specific dimensions of leading for learning are presented: values and beliefs, leadership focus, contexts for leadership, and sharing leadership. Design/methodology/approach The paper employs a review methodology but focuses especially on evidence from several recent empirical studies. While the author argues that progress has been made, limitations – especially with respect to linking leadership practice to different contexts – are noted. Findings The paper finds that significant progress has been made in identifying the means by which leadership impacts on learning. Research limitations/implications The key limitation in this research lies in the difficulty in linking leadership to its context. While progress is also beginning to be made in this area, it remains a limiting factor in interpreting the findings from this body of research. Practical implications The above limitation means that individual school leaders must still apply the findings both with caution and with an understanding of their own particular school context. Originality/value The paper extends prior reviews by its inclusion of findings from a series of important studies that have emerged since 2008.

Americanae nace como un proyecto conjunto que surge dentro de la Red Europea de Información y Documentación sobre América Latina (REDIAL), y que ha afrontado la Biblioteca de la Agencia Española de Cooperación Internacional para el Desarrollo (AECID). Esta nueva biblioteca virtual hace más accesibles los libros digitales de tema americanista a los investigadores y usuarios interesados de cualquier parte del mundo.

Considering the increasing importance of Artificial Intelligence in Education (AIEd) and the absence of a comprehensive review on it, this research aims to conduct a comprehensive and systematic review of influential AIEd studies. We analyzed 45 articles in terms of annual distribution, leading journals, institutions, countries/regions, the most frequently used terms, as well as theories and technologies adopted. We also evaluated definitions of AIEd from broad and narrow perspectives and clarified the relationship among AIEd, Educational Data Mining, Computer-Based Education, and Learning Analytics. Results indicated that: 1) there was a continuingly increasing interest in and impact of AIEd research; 2) little work had been conducted to bring deep learning technologies into educational contexts; 3) traditional AI technologies, such as natural language processing were commonly adopted in educational contexts, while more advanced techniques were rarely adopted, 4) there was a lack of studies that both employ AI technologies and engage deeply with educational theories. Findings suggested scholars to 1) seek the potential of applying AI in physical classroom settings; 2) spare efforts to recognize detailed entailment relationships between learners’ answers and the desired conceptual understanding within intelligent tutoring systems; 3) pay more attention to the adoption of advanced deep learning algorithms such as generative adversarial network and deep neural network; 4) seek the potential of NLP in promoting precision or personalized education; 5) combine biomedical detection and imaging technologies such as electroencephalogram, and target at issues regarding learners’ during the learning process; and 6) closely incorporate the application of AI technologies with educational theories.

We aimed to establish the vocabulary learning strategies used by Chinese university learners of English and the relationship between their strategies and outcomes in learning English. We asked 850 sophomore non‐English majors at Beijing Normal University to complete a vocabulary learning questionnaire. We correlated replies to the questionnaire with results on a vocabulary size test and on the College English Test (CETBAND2). Participants reported using a wide variety of vocabulary learning strategies. In a multiple regression analysis, Self‐Initiation and Selective Attention, two metacognitive strategies, emerged as positive predictors of CETBAND2 scores. Contextual guessing, skillful use of dictionaries, note‐taking, paying attention to word formation, contextual encoding, and activation of newly learned words also positively correlated with the two test scores. However, visual repetition of new words was the strongest negative predictor of both vocabulary size and general proficiency. Furthermore, strategies aiming at vocabulary retention only related more to vocabulary size than to English proficiency. We identified 5 approaches to learning. These strategy combinations, rather than individual strategies, may have made the difference in these people's learning.

It has been demonstrated that combining the decisions of several classifiers can lead to better recognition results. The combination can be implemented using a variety of strategies, among which majority vote is by far the simplest, and yet it has been found to be just as effective as more complicated schemes in improving the recognition results. This paper examines the mode of operation of the majority vote method in order to gain a deeper understanding of how and why it works, so that a more solid basis can be provided for its future applications to different data and/or domains. In the course of our research, we have analyzed this method from its foundations and obtained many new and original results regarding its behavior. Particular attention has been directed toward the changes in the correct and error rates when classifiers are added, and conditions are derived under which their addition/elimination would be valid for the specific objectives of the application. At the same time, our theoretical findings are compared against experimental results, and these results do reflect the trends predicted by the theoretical considerations.

OBJECTIVE: A sense of belonging-the subjective feeling of deep connection with social groups, physical places, and individual and collective experiences-is a fundamental human need that predicts numerous mental, physical, social, economic, and behavioural outcomes. However, varying perspectives on how belonging should be conceptualised, assessed, and cultivated has hampered much-needed progress on this timely and important topic. To address these critical issues, we conducted a narrative review that summarizes existing perspectives on belonging, describes a new integrative framework for understanding and studying belonging, and identifies several key avenues for future research and practice. METHOD: We searched relevant databases, including Google Scholar, PubMed, Scopus, PsycInfo, and ClinicalTrials.gov, for articles describing belonging, instruments for assessing belonging, and interventions for increasing belonging. RESULTS: By identifying the core components of belonging, we introduce a new integrative framework for understanding, assessing, and cultivating belonging that focuses on four interrelated components: competencies, opportunities, motivations, and perceptions. CONCLUSION: This integrative framework enhances our understanding of the basic nature and features of belonging, provides a foundation for future interdisciplinary research on belonging and belongingness, and highlights how a robust sense of belonging may be cultivated to improve human health and resilience for individuals and communities worldwide.

There has been a remarkable growth of interest in the theory and practice of autonomy in language teaching and learning in recent years. Focusing on work published since the turn of the 20th century, this review examines major trends in the recent literature on autonomy related to the emergence of alternative views of autonomy, new contexts of practice and interaction with concepts such as self-regulation, motivation, sociocultural theory and teacher development. The review also covers relevant developments in the philosophy of autonomy and the role of autonomy in global educational policy and reform. It concludes by discussing possible directions for future research in the field.

(2007). English as a Lingua Franca: Attitude and Identity. Asian Englishes: Vol. 10, No. 2, pp. 106-109.

The development of an artificial photosynthetic system is a promising strategy to convert solar energy into chemical fuels. Here, a direct Z-scheme CdS-WO(3) photocatalyst without an electron mediator is fabricated by imitating natural photosynthesis of green plants. Photocatalytic activities of as-prepared samples are evaluated on the basis of photocatalytic CO(2) reduction to form CH(4) under visible light irradiation. These Z-scheme-heterostructured samples show a higher photocatalytic CO(2) reduction than single-phase photocatalysts. An optimized CdS-WO(3) heterostructure sample exhibits the highest CH(4) production rate of 1.02 μmol h(-1) g(-1) with 5 mol% CdS content, which exceeds the rates observed in single-phase WO(3) and CdS samples for approximately 100 and ten times under the same reaction condition, respectively. The enhanced photocatalytic activity could be attributed to the formation of a hierarchical direct Z-scheme CdS-WO(3) photocatalyst, resulting in an efficient spatial separation of photo-induced electron-hole pairs. Reduction and oxidation catalytic centers are maintained in two different regions to minimize undesirable back reactions of the photocatalytic products. The introduction of CdS can enhance CO(2) molecule adsorption, thereby accelerating photocatalytic CO(2) reduction to CH(4). This study provides novel insights into the design and fabrication of high-performance artificial Z-scheme photocatalysts to perform photocatalytic CO(2) reduction.

Fifty years of theory and research offer increasing levels of support for the assertion that principal leadership makes a difference in the quality of schooling, school development, and student learning. In the current context of global education reform, however, recent inquiries have focused on identifying how teams of school leaders contribute to school improvement and student learning. This paper reports findings drawn from a series of empirical analyses that assessed the effects of collaborative leadership on school improvement capacity and student learning in a large sample of US primary schools over a four-year period. Our findings support the prevailing view that collaborative school leadership can positively impact student learning in reading and math through building the school's capacity for academic improvement. The research extends this finding, however, by offering empirical support for a more refined conception that casts leadership for student learning as a process of mutual influence in which school capacity both shapes and is shaped by the school's collective leadership.

The purpose of this study was to develop an instrument to measure perceived teacher efficacy to teach in inclusive classrooms. An 18‐item scale was developed on a sample of 607 pre‐service teachers selected from four countries (Canada, Australia, Hong Kong and India). Factor analysis of responses from the sample revealed three factors: efficacy in using inclusive instruction, efficacy in collaboration and efficacy in dealing with disruptive behaviours. The alpha coefficient for the total scale was 0.89. Alpha coefficients for the three factors ranged from 0.85 to 0.93. Reliability analysis for the total scale as well as factors for each country suggested that the scale provides a reliable measure of pre‐service teacher perceptions of self‐efficacy for inclusion across different countries.