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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.
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Classification of electroencephalogram (EEG) is a key approach to measure the rhythmic oscillations of neural activity, which is one of the core technologies of brain-computer interface systems (BCIs). However, extraction of the features from non-linear and non-stationary EEG signals is still a challenging task in current algorithms. With the development of artificial intelligence, various advanced algorithms have been proposed for signal classification in recent years. Among them, deep neural networks (DNNs) have become the most attractive type of method due to their end-to-end structure and powerful ability of automatic feature extraction. However, it is difficult to collect large-scale datasets in practical applications of BCIs, which may lead to overfitting or weak generalizability of the classifier. To address these issues, a promising technique has been proposed to improve the performance of the decoding model based on data augmentation (DA). In this article, we investigate recent studies and development of various DA strategies for EEG classification based on DNNs. The review consists of three parts: what kind of paradigms of EEG-based on BCIs are used, what types of DA methods are adopted to improve the DNN models, and what kind of accuracy can be obtained. Our survey summarizes the current practices and performance outcomes that aim to promote or guide the deployment of DA to EEG classification in future research and development.
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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.
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This commentary reviews recent research in terms of tourist’s mobilities in terms practices of walking, cycling and driving. It concludes by reflecting on the contemporary lock down of travel in terms of the global pandemic and its consequences for waiting, stillness and immobility – particularly in terms of flying.
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Consumers' selections and decision-making processes are some of the most exciting and challenging topics in neuromarketing, sales, and branding. From a global perspective, multicultural influences and societal conditions are crucial to consider. Neuroscience applications in international marketing and consumer behavior is an emergent and multidisciplinary field aiming to understand consumers' thoughts, reactions, and selection processes in branding and sales. This study focuses on real-time monitoring of different physiological signals using eye-tracking, facial expressions recognition, and Galvanic Skin Response (GSR) acquisition methods to analyze consumers' responses, detect emotional arousal, measure attention or relaxation levels, analyze perception, consciousness, memory, learning, motivation, preference, and decision-making. This research aimed to monitor human subjects' reactions to these signals during an experiment designed in three phases consisting of different branding advertisements. The nonadvertisement exposition was also monitored while gathering survey responses at the end of each phase. A feature extraction module with a data analytics module was implemented to calculate statistical metrics and decision-making supporting tools based on Principal Component Analysis (PCA) and Feature Importance (FI) determination based on the Random Forest technique. The results indicate that when compared to image ads, video ads are more effective in attracting consumers' attention and creating more emotional arousal.
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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.
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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.
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This study investigates career trajectory and work locations of doctoral students trained in Macao and analyses how their career paths are shaped by perceived macro-level factors. Respondents from four applied disciplinary areas were selected for semi-structured in-depth interviews. Research results show that doctoral students who graduated from Macao higher education institutions enjoy good career prospects in Mainland China. Their competitiveness in the research-related job market benefits from having a multi-level support system and a training mode that promotes government–university–industry collaboration. Policies and demand from industrial sectors are involved in students' learning experience through channels such as financial support, project collaboration and networks. Doctoral students in Macao are strategic planners and actors in leveraging their human capital. As Macao becomes an emerging destination for cultivating high-level research labour, findings from this study capture a model of human capital formation in China's cross-system context.
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A growing focus on God’s mercy and forgiveness emerged in the wake of the recent Pontificates of John Paul II, Benedict XVI, and Francis. Our time with its multiple crises cries for healing, forgiveness, and the experience of God’s mercy. In social, political, and global terms, humanity craves for “lasting peace, born of the marriage of justice and mercy” (John Paul II, 2001, no. 15). The experience of God’s forgiveness, merciful healing and new life has been expressed many times in the Bible. But, theologically, it has never been formulated as directly as in Hosea 11:8, when God’s own heart becomes “turned over”, “converted” following the blaze of his own overwhelming compassion, paving the way for a fundamental spiritual transformation, rooted in forgiveness and mercy, that opens wellsprings of dignity, healing, and new life for all.
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The article sets off from a speech given by Benedict XVI in the German Bundestag in 2011, where he requested an ecological learning process to aim at sustainable human development. Appreciating the Ecological Movement, he asked to learn to listen to Nature’s language and act accordingly, which he applies analogically to “human ecology”. The article bridges elements of “Listening to Nature” and the Natural Moral Law Tradition in Benedict’s speech and in Francis’ Encyclical Letter Laudatu Si’ inview of serving human flourishing in an ecological civilization. Keywords: Natural Moral Law; Nature, Laudatu Si’, Benedict XVI, Francis; Ecological Civilization/生態文明, Sustainable Development, Ecology of Man.
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Artists are increasingly using blockchain as a tool for trading digital artwork as non-fungible tokens (NFTs); however, some are also beginning to experiment with the blockchain as a medium for generative art, using it as a seed for a generative process or to continuously modify an evolving piece. This paper surveys, reviews, and classifies the state-of-the-art in blockchain-interactive NFTs and presents a liberal-arts critique of the opportunities and threats posed by this technology, whilst addressing existing criticism on the broader topic of art-related NFTs. The paper examines some of the most experimental pieces minted on the Hic et Nunc (HEN) and Teia NFT marketplaces, for which a purpose-built research tool was developed. The survey reveals some reliance on centralised infrastructure, namely blockchain indexers, placing undesired trust on third parties which undermines the potential longevity of the artwork. The paper concludes with recommendations for artists and NFT platform designers for developing more resilient and economically sustainable architectures.
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The concept of Soundscape was initially proposed to study the relationship between humans and their sonic environment. It has gathered momentum from academia to environmentalists and policymakers throughout the years. The study and characterisation of Soundscapes can be complex as it tries to take a holistic and qualitative approach rather than simply quantifying sound pressure levels. This paper introduces a comprehensive Soundscape study process in an ongoing research project in Macao (China), a small territory (32.9 km2) and one of the most densely populated areas in the world. The paper seeks to show a first version of a technical solution to systematically capture the local soundscape, analyse it, classify it, and ultimately deliver a dataset library and the intangible qualities of the environmental sound. This implementation, including technical documentation, code, and sound library with strong labelling, is presented under an open-source license to encourage future collaborative research. Finally, the paper offers suggestions on further developing the apparatus to reach a systematic and near real-time soundscape analysis with the development of a machine learning system.
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It is plausible to assume that the component waves in ECG signals constitute a unique human characteristic because morphology and amplitudes of recorded beats are governed by multiple individual factors. According to the best of our knowledge, the issue of automatically classifying different ’identities’ of QRS morphology has not been explored within the literature. This work proposes five alternative mathematical models for representing different QRS morphologies providing the extraction of a set of features related to QRS shape. The technique incorporates mechanisms of combining the mathematical functions Gaussian, Mexican-Hat and Rayleigh probability density function and also a mechanism for clipping the waveform of those functions. The searching for the optimal parameters which minimize the normalized RMS error between each mathematical model and a given QRS search window enables to find an optimal model. Such modeling behaves as a robust alternative for delineating heartbeats, classifying beat morphologies, detecting subtle and anomalous changes, compression of QRS complex windows among others. The validation process evaluates the ability of each model to represent different QRS morphology classes within 159 full ECG signal records from QT database and 584 QRS search windows from MIT-BIH Arrhythmia database. From the experimental results, we rank the winning rates for which each mathematical model best models and also discriminates the most predominant QRS morphologies Rs, rS, RS, qR, qRs, R, rR’s and QS. Furthermore, the average time errors computed for QRS onset and offset locations when using the corresponding winner mathematical models for delineation purposes were, respectively, 12.87±8.5 ms and 1.47±10.06 ms.
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The recently explored inactive Tianzuo hydrothermal field, in the amagmatic segment of the ultraslow-spreading Southwest Indian Ridge (SWIR), is closely associated with detachment faults. In this site, sulfide minerals are hosted by serpentine-bearing ultramafic rocks and include high-temperature (isocubanite, sphalerite, and minor pyrrhotite) and low-temperature (pyrite I, marcasite, pyrite II, and covellite) phases. In this study, trace-element concentrations of isocubanite and pyrite II were used to elucidate mineralization processes in ultramafic rocks hosting sulfides. Results show that isocubanite is enriched in metals such as Cu, Co, Sn, Te, Zn, Se, Pb, Bi, Cd, Ag, In, and Mn, and pyrite II is enriched in Mo and Tl. The marked enrichment in Te, Cu, Co, and In in isocubanite (compared with Se, Zn, Ni, and Sn, respectively) is most likely due to the contribution of magmatic fluids from gabbroic intrusions beneath the hydrothermal field. The intrusion of gabbroic magmas would have enhanced serpentinization reactions and provided a relatively oxidizing environment through the dissolution of anhydrite precipitated previously in the reaction zone, within high temperature and low pH conditions. This might have facilitated the extraction of metals by initial hydrothermal fluids, leading to the general enrichment of most metals in isocubanite. Metals in pyrite II have compositions similar to those of isocubanite, except for strong depletion in magmatically derived Te, Cu, Co, and In. This means that serpentinization processes had a dominating role in pyrite II precipitation as well. The enrichment of pyrite II in Mo and Tl is also indicative of seawater contribution in its composition. The study concludes that serpentinization reactions contribute effectively both to high- and low-temperature sulfide mineralization at Tianzuo hydrothermal field, with gabbroic intrusions further promoting high-temperature sulfide mineralization, providing additional metals, fluids and heat. In contrast, low-temperature sulfide mineralization occurred during the cooling of gabbroic intrusions, with decreasing rates of serpentinization reactions and a significant influence of seawater.
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