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Since the launch of the One Belt and One Road Initiative (BRI) in 2013, the internationalisation of China’s tertiary education has entered a new stage. Central to the BRI is investment and strategic planning for talent cultivation, knowledge production, and transmission. This paper explains how the BRI redirects, reinforces, and intensifies China’s strategic planning and actions for internationalising its education. It adopts a policy analysis approach and reviews three key aspects of development and shifting emphasis of internationalisation under the impact of the BRI: international education networks along the Six BRI Economic Corridors, vocational colleges as new players in international education, and promotion of the Chinese language as a new global language. The analysis captures an important moment in which international education processes are being visibly altered through China’s strategies to take the lead in economic globalisation and to compete for a central place in the world via the BRI.

This contribution to the special issue is an historical account of Paulo Freire’s pedagogical and administrative praxis before his forced exile in 1964. It relies on interviews collected during a field trip in 1976, a conversation with Paulo Freire in Geneva one year later and on the secondary literature up to date. Being the head of the first Extension Service of a major Brazilian university in the early 1960s gave Freire and his collaborators the space and time to experiment with the today world famous literacy method bearing his name. The concept of ‘Field of Cultural Production’ (Bourdieu) is used to elucidate better Freire and his team’s avant-gardist production within the spaces opened up by Brazil’s popular movements in the early sixties. The contribution shows how the ‘Paulo Freire System’ developed in the praxis of a cultural movement and received its academic consecration in an incremental and eclectic style.

In a context of a new transnational division of labour, temporary international labour mobility is on the rise in Europe. In particular, recent decades have seen considerably more women seeking work experience abroad. Observers have been concerned with how such mobility is related to individualization, and in particular how it may challenge collective institutions, communities and families. The aim of this study is to explore such issues among women and men with international work experience. Using data from European Social Survey, the paper investigates previously mobile workers in terms of their current working and living conditions. Across genders, we consider different forms of individualization that may be associated with transnational labour mobility. While both women and men with transnational work experience generally feature strong strategic individualization, this is most pronounced among men. Hence, men's mobility is among other things associated with increased autonomy in working life, while – in contrast to women – it does not seem to hamper their integration in the sphere of social reproduction.

The key challenge of Unsupervised Domain Adaptation (UDA) for analyzing time series data is to learn domain-invariant representations by capturing complex temporal dependencies. In addition, existing unsupervised domain adaptation methods for time series data are designed to align marginal distribution between source and target domains. However, existing UDA methods (e.g. R-DANN Purushotham et al. (2017), VRADA Purushotham et al. (2017), CoDATS Wilson et al. (2020)) neglect the conditional distribution discrepancy between two domains, leading to misclassification of the target domain. Therefore, to learn domain-invariant representations by capturing the temporal dependencies and to reduce the conditional distribution discrepancy between two domains, a novel Attentive Recurrent Adversarial Domain Adaptation with Top-k time series pseudo-labeling method called ARADA-TK is proposed in this paper. In the experiments, our proposed method was compared with the state-of-the-art UDA methods (R-DANN, VRADA and CoDATS). Experimental results on four benchmark datasets revealed that ARADA-TK achieves superior classification accuracy when it is compared to the competing methods.

Stock movement prediction is one of the most challenging problems in time series analysis due to the stochastic nature of financial markets. In recent years, a plethora of statistical methods and machine learning algorithms were proposed for stock movement prediction. Specifically, deep learning models are increasingly applied for the prediction of stock movement. The success of deep learning models relies on the assumption that massive training data are available. However, this assumption is impractical for stock movement prediction. In stock markets, a large number of stocks do not have enough historical data, especially for the companies which underwent initial public offering in recent years. In these situations, the accuracy of deep learning models to predict the stock movement could be affected. To address this problem, in this paper, we propose novel instance-based deep transfer learning models with attention mechanism. In the experiments, we compare our proposed methods with state-of-the-art prediction models. Experimental results on three public datasets reveal that our proposed methods significantly improve the performance of deep learning models when limited training data are available.

Despite the prevalence of aesthetic education as one of the main developmental objectives in curricular worldwide, the mainstream philosophical discourse on its definition is predominately framed by western philosophy due to a paucity of cross-cultural studies on the subject. The article aims to achieve a contemporary understanding of aesthetic education from both the Chinese and Western aesthetic perspectives. Through the lens of postmodernism, the relationship between Daoist aesthetics and the western postmodern aesthetic perspectives, particularly the Deleuzian concept of rhizome, is identified. Both aesthetic perspectives concern de-authorship and promote self-consciousness/self-awareness. The study reconceptualises the functions of aesthetic education with the Chinese aesthetic philosophy that promotes the nurture of better people through benevolence.

Various materials, objects, and sensors have been explored earlier for creating tangible user interfaces (TUIs). However, there is little work on 3D-printed TUIs based on visual markers for smartphone-based extended reality (XR) experiences. The combination of visual markers and smartphones results in cheap, accessible XR systems within reach of many people. Combined with 3D printing, it could foster do-it-yourself (DIY) projects for XR experiences, which may further expand and open-up possibilities for accessible and tangible interaction. This work explores the design space of modular 3D-printed tangibles for smartphone-based XR. The authors report the design exploration process, provide several interactive 3D-printed markers, and reflect on the resulting possibilities.

In government studies, electronic government has become a hot topic in recent decades. Many scholars believe that soon, the government might not be able to operate smoothly without the help of ICTs as the Internet has been overwhelming people's daily lives already. In analyzing people's behavioral factors towards adopting e-government services, most studies targeted the adult population, while those in the hard-to-reach groups are minimal. This study was designed especially to understand the behavioral factors of the younger generation aged between 18 and 24 and the senior citizens above 60 on their adoption of e-government services in Macao SAR. Sixteen in-depth interviews were conducted based on the semi-structured interview questions developed from the prior literature on the Theory of Planned Behavior and e-government studies. Six significant findings are yielded, which could serve as an important reference for policymakers designing e-government policy and promoting its implementation strategy. These behavioral factors also contribute empirical data to support the theoretical framework of TPB in the context of Macao SAR e-government services.

Genotoxic effects of dicofol on the edible clam Meretrix meretrix were investigated through a mesocosm experiment. Individuals of M. meretrix, were exposed to environmental concentration (D1 = 50 ng/L) and supra-environmental concentration (D2 = 500 ng/L) of dicofol for 15 days, followed by the same depuration period. DNA damage (i.e., strand breaks and alkali-labile sites) was evaluated at day 1, 7 and 15, during uptake and depuration, using Comet assay (alkaline version) and nuclear abnormalities (NAs) as genotoxicity biomarkers. The protective effects of dicofol against DNA damage induced by ex vivo hydrogen peroxide (H2O2) exposure were also assessed. Comet assay results revealed no significant DNA damages under dicofol exposure, indicating 1) apparent lack of genotoxicity of dicofol to the tested conditions and/or 2) resistance of the animals due to optimal adaptation to stress conditions. Moreover, ex vivo H2O2 exposure showed an increase in the DNA damage in all the treatments without significant differences between them. However, considering only the DNA damage induced by H2O2 during uptake phase, D1 animals had significantly lower DNA damage than those from other treatments, revealing higher protection against a second stressor. NAs data showed a decrease in the % of cells with polymorphic, kidney shape, notched or lobbed nucleus, along the experiment. The combination of these results supports the idea that the clams used in the experiment were probably collected from a stressful environment (in this case Pearl River Delta region) which could have triggered some degree of adaptation to those environmental conditions, explaining the lack of DNA damages and highlighting the importance of organisms’ origin and the conditions that they were exposed during their lives.

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

Social workers’ work engagement and burnout were tested in relation to (a) personal variable, i.e., emotional intelligence; (b) organizational variables, i.e., work satisfaction and affective commitment. Regressions revealed emotional intelligence - controlling self – negatively predicted depersonalization and reduced personal accomplishment and positively predicted three facets of work engagement. Emotional intelligence - understanding others – was a negative predictor of reduced personal accomplishment. In addition, work satisfaction negatively predicted three components of burnout and positively predicted emotional work engagement. Affective commitment was a positive predictor of three facets of work engagement and negatively predicted reduced personal accomplishment. Implications for management are discussed.

Background This study aimed to investigate English teachers’ self-efficacy for student engagement, classroom management, instructional strategies and literacy instruction, as well as to discover teacher stress and job satisfaction can play a role in interfering their occupational health (in terms of self-efficacy). In addition, this is one of the first studies to understand the differences in self-efficacy among pre-service, novice and experienced in-service teachers in a Chinese society, where English is positioned as a foreign language. Participants and procedure 271 English teachers (90 pre-service, 181 in-service) with mean teaching experience of 5.57 months for per-service, and 98.51 months for in-service were participated in this quantitative research study, as the targets were not be able to approach randomly, the English teachers were approaching individually though referral sampling, informing that the purpose of the study and receive their consent. Results It discovered both pre-service and novice in-service teachers posses lowest self-efficacy. Moreover, teachers’ stress from classroom predicted their self-efficacy for student engagement and classroom management negatively. On the other hand, teachers’ job satisfaction predicts their self-efficacy for student engagement, instructional strategies and literacy instruction positively. Conclusions Implications (based on the findings) are discussed in order to provide insights for for schools and education departments to strengthen the teachers’ capability of teaching and their occupational health.

Anthropogenic noise can be hazardous for the auditory system and wellbeing of animals, including humans. However, very limited information is known on how this global environmental pollutant affects auditory function and inner ear sensory receptors in early ontogeny. The zebrafish (Danio rerio) is a valuable model in hearing research, including investigations of developmental processes of the vertebrate inner ear. We tested the effects of chronic exposure to white noise in larval zebrafish on inner ear saccular sensitivity and morphology at 3 and 5 days post-fertilization (dpf), as well as on auditory-evoked swimming responses using the prepulse inhibition (PPI) paradigm at 5 dpf. Noise-exposed larvae showed a significant increase in microphonic potential thresholds at low frequencies, 100 and 200 Hz, while the PPI revealed a hypersensitization effect and a similar threshold shift at 200 Hz. Auditory sensitivity changes were accompanied by a decrease in saccular hair cell number and epithelium area. In aggregate, the results reveal noise-induced effects on inner ear structure–function in a larval fish paralleled by a decrease in auditory-evoked sensorimotor responses. More broadly, this study highlights the importance of investigating the impact of environmental noise on early development of sensory and behavioural responsiveness to acoustic stimuli.

The manifestation of generating digital visuals through an algorithm is gaining worldwide attention in the graphic design industry. It is a new form of computing that visualizes data input by the designer or collected in the physical environment and turns them into artwork. The generative design of...

Despite the levels of air pollution in Macao continuing to improve over recent years, there are still days with high-pollution episodes that cause great health concerns to the local community. Therefore, it is very important to accurately forecast air quality in Macao. Machine learning methods such as random forest (RF), gradient boosting (GB), support vector regression (SVR), and multiple linear regression (MLR) were applied to predict the levels of particulate matter (PM10 and PM2.5) concentrations in Macao. The forecast models were built and trained using the meteorological and air quality data from 2013 to 2018, and the air quality data from 2019 to 2021 were used for validation. Our results show that there is no significant difference between the performance of the four methods in predicting the air quality data for 2019 (before the COVID-19 pandemic) and 2021 (the new normal period). However, RF performed significantly better than the other methods for 2020 (amid the pandemic) with a higher coefficient of determination (R2) and lower RMSE, MAE, and BIAS. The reduced performance of the statistical MLR and other ML models was presumably due to the unprecedented low levels of PM10 and PM2.5 concentrations in 2020. Therefore, this study suggests that RF is the most reliable prediction method for pollutant concentrations, especially in the event of drastic air quality changes due to unexpected circumstances, such as a lockdown caused by a widespread infectious disease.

Objective. As the preclinical stage of Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI) is characterized by hidden onset, which is difficult to detect early. Traditional neuropsychological scales are main tools used for assessing MCI. However, due to its strong subjectivity and the influence of many factors such as subjects’ educational background, language and hearing ability, and time cost, its accuracy as the standard of early screening is low. Therefore, the purpose of this paper is to propose a new key technology of fast digital early warning for MCI based on eye movement objective data analysis. Methodology. Firstly, four exploratory indexes (test durations, correlation degree, lengths of gaze trajectory, and drift rate) of MCI early warning are determined based on the relevant literature research and semistructured expert interview; secondly, the eye movement state is captured based on the eye tracker to realize the data extraction of four exploratory indexes. On this basis, the human-computer interactive 2.5-minute fast digital early warning paradigm for MCI is designed; thirdly, the rationality of the four early warning indexes proposed in this paper and their early warning effectiveness on MCI are verified. Results. Through the small sample test of human-computer interactive 2.5 fast digital early warning paradigm for MCI conducted by 32 elderly people aged 70–90 in a medical institution in Hangzhou, the two indexes of “correlation degree” and “drift rate” with statistical differences are selected. The experiment results show that AUC of this MCI early warning paradigm is 0.824. Conclusion. The key technology of human-computer interactive 2.5 fast digital early warning for MCI proposed in this paper overcomes the limitations of the existing MCI early warning tools, such as low objectification level, high dependence on professional doctors, long test time, requiring high educational level, and so on. The experiment results show that the early warning technology, as a new generation of objective and effective digital early warning tool, can realize 2.5-minute fast and high-precision preliminary screening and early warning for MCI in the elderly.