Showing papers by "Dublin City University published in 2020"
TL;DR: In this article, the volatility relationship between the main Chinese stock markets and Bitcoin evolved significantly during this period of enormous financial stress, and the authors provided a number of observations as to why this situation occurred.
591 citations
Anadolu University1, International Christian University2, Deakin University3, Princess Nora bint Abdul Rahman University4, University of the Republic5, National Scientific and Technical Research Council6, American University in Cairo7, Far Eastern University8, University of South Africa9, University of Minnesota10, Open University of Catalonia11, Aristotle University of Thessaloniki12, Lille University of Science and Technology13, Dublin City University14, Oklahoma State University–Stillwater15, Monterrey Institute of Technology and Higher Education16, University College London17, University of Béjaïa18, University of Victoria19, Ambedkar University Delhi20, University of Cambridge21, Fontys University of Applied Sciences22, National University of the Littoral23, University of Perpignan24, École Polytechnique25
TL;DR: In this paper, the authors present a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population.
Abstract: Uncertain times require prompt reflexes to survive and this study is a collaborative reflex to better understand uncertainty and navigate through it. The Coronavirus (Covid-19) pandemic hit hard and interrupted many dimensions of our lives, particularly education. As a response to interruption of education due to the Covid-19 pandemic, this study is a collaborative reaction that narrates the overall view, reflections from the K-12 and higher educational landscape, lessons learned and suggestions from a total of 31 countries across the world with a representation of 62,7% of the whole world population. In addition to the value of each case by country, the synthesis of this research suggests that the current practices can be defined as emergency remote education and this practice is different from planned practices such as distance education, online learning or other derivations. Above all, this study points out how social injustice, inequity and the digital divide have been exacerbated during the pandemic and need unique and targeted measures if they are to be addressed. While there are support communities and mechanisms, parents are overburdened between regular daily/professional duties and emerging educational roles, and all parties are experiencing trauma, psychological pressure and anxiety to various degrees, which necessitates a pedagogy of care, affection and empathy. In terms of educational processes, the interruption of education signifies the importance of openness in education and highlights issues that should be taken into consideration such as using alternative assessment and evaluation methods as well as concerns about surveillance, ethics, and data privacy resulting from nearly exclusive dependency on online solutions.
452 citations
Universidade Federal de Minas Gerais1, University of Split2, Technische Universität München3, University of Münster4, University of Colombo5, University of Peradeniya6, University of Newcastle7, National Institute for Medical Research8, Federal University of São Paulo9, Cochrane Collaboration10, York University11, Lund University12, University of Toledo13, The George Institute for Global Health14, Wuhan University15, Dublin City University16, Ohio State University17
TL;DR: The majority of reported clinical symptoms and laboratory findings related to SARS-CoV-2 infection are non-specific and clinical suspicion, accompanied by a relevant epidemiological history, should be followed by early imaging and virological assay.
Abstract: A growing body of literature on the 2019 novel coronavirus (SARS-CoV-2) is becoming available, but a synthesis of available data has not been conducted. We performed a scoping review of currently available clinical, epidemiological, laboratory, and chest imaging data related to the SARS-CoV-2 infection. We searched MEDLINE, Cochrane CENTRAL, EMBASE, Scopus and LILACS from 01 January 2019 to 24 February 2020. Study selection, data extraction and risk of bias assessment were performed by two independent reviewers. Qualitative synthesis and meta-analysis were conducted using the clinical and laboratory data, and random-effects models were applied to estimate pooled results. A total of 61 studies were included (59,254 patients). The most common disease-related symptoms were fever (82%, 95% confidence interval (CI) 56%–99%; n = 4410), cough (61%, 95% CI 39%–81%; n = 3985), muscle aches and/or fatigue (36%, 95% CI 18%–55%; n = 3778), dyspnea (26%, 95% CI 12%–41%; n = 3700), headache in 12% (95% CI 4%–23%, n = 3598 patients), sore throat in 10% (95% CI 5%–17%, n = 1387) and gastrointestinal symptoms in 9% (95% CI 3%–17%, n = 1744). Laboratory findings were described in a lower number of patients and revealed lymphopenia (0.93 × 109/L, 95% CI 0.83–1.03 × 109/L, n = 464) and abnormal C-reactive protein (33.72 mg/dL, 95% CI 21.54–45.91 mg/dL; n = 1637). Radiological findings varied, but mostly described ground-glass opacities and consolidation. Data on treatment options were limited. All-cause mortality was 0.3% (95% CI 0.0%–1.0%; n = 53,631). Epidemiological studies showed that mortality was higher in males and elderly patients. The majority of reported clinical symptoms and laboratory findings related to SARS-CoV-2 infection are non-specific. Clinical suspicion, accompanied by a relevant epidemiological history, should be followed by early imaging and virological assay.
432 citations
TL;DR: A general Contrastive Representation Learning framework is proposed that simplifies and unifies many different contrastive learning methods and a taxonomy for each of the components is provided in order to summarise and distinguish it from other forms of machine learning.
Abstract: Contrastive Learning has recently received interest due to its success in self-supervised representation learning in the computer vision domain. However, the origins of Contrastive Learning date as far back as the 1990s and its development has spanned across many fields and domains including Metric Learning and natural language processing. In this paper, we provide a comprehensive literature review and we propose a general Contrastive Representation Learning framework that simplifies and unifies many different contrastive learning methods. We also provide a taxonomy for each of the components of contrastive learning in order to summarise it and distinguish it from other forms of machine learning. We then discuss the inductive biases which are present in any contrastive learning system and we analyse our framework under different views from various sub-fields of Machine Learning. Examples of how contrastive learning has been applied in computer vision, natural language processing, audio processing, and others, as well as in Reinforcement Learning are also presented. Finally, we discuss the challenges and some of the most promising future research directions ahead.
359 citations
TL;DR: As Tether successfully maintained its peg to the US dollar during the COVID-19 turmoil, it acted as a safe haven investment for all of the international indices examined.
333 citations
TL;DR: In this paper, the authors define dynamic capability as the potential to systematically solve problems, enabled by its propensity to sense opportunities and threats, to make timely decisions, and to implement strategic decisions and changes efficiently, thereby ensuring the right direction.
260 citations
19 Jul 2020
TL;DR: FjQsC as discussed by the authors proposes to learn from unlabeled data by generating soft pseudo-labels using the network predictions, which achieves state-of-the-art results in CIFAR-10/100, SVHN, and Mini-ImageNet despite being much simpler than other methods.
Abstract: Semi-supervised learning, i.e. jointly learning from labeled and unlabeled samples, is an active research topic due to its key role on relaxing human supervision. In the context of image classification, recent advances to learn from unlabeled samples are mainly focused on consistency regularization methods that encourage invariant predictions for different perturbations of unlabeled samples. We, conversely, propose to learn from unlabeled data by generating soft pseudo-labels using the network predictions. We show that a naive pseudo-labeling overfits to incorrect pseudo-labels due to the so-called confirmation bias and demonstrate that mixup augmentation and setting a minimum number of labeled samples per mini-batch are effective regularization techniques for reducing it. The proposed approach achieves state-of-the-art results in CIFAR-10/100, SVHN, and Mini-ImageNet despite being much simpler than other methods. These results demonstrate that pseudo-labeling alone can outperform consistency regularization methods, while the opposite was supposed in previous work. Source code is available at https://git.io/fjQsC.
209 citations
TL;DR: Evidence of significant growth in both returns and volumes traded is found, indicating that large cryptocurrencies acted as a store of value during this period of exceptional financial market stress, and results suggest that these digital assets acting as a safe-haven similar to that of precious metals during historic crises.
160 citations
TL;DR: In this paper, the authors argue that human resource management has a potentially vital role to play in contributing to a firm's CS/CSR efforts, but so far has failed to deliver.
154 citations
TL;DR: Positive and economically meaningful spillovers from falling oil prices to both renewable energy and coal markets are found, however, this result is only found for the narrow portion of the authors' sample surrounding the negative WTI event.
146 citations
TL;DR: The authors presents a compilation of personal reflections from 66 contributors on the impact of and responses to, COVID-19 in accounting education in 45 different countries around the world and identifies issues that need to be addressed in the recovery and redesign stages of the management of this crisis.
Abstract: This paper presents a compilation of personal reflections from 66 contributors on the impact of, and responses to, COVID-19 in accounting education in 45 different countries around the world. It reveals a commonality of issues, and a variability in responses, many positive outcomes, including the creation of opportunities to realign learning and teaching strategies away from the comfort of traditional formats, but many more that are negative, primarily relating to the impact on faculty and student health and well-being, and the accompanying stress. It identifies issues that need to be addressed in the recovery and redesign stages of the management of this crisis, and it sets a new research agenda for studies in accounting education.
TL;DR: This review details emerging trends in nanotechnology to specifically target wound healing applications and particular focus is given to the most common natural polymers that could address many unmet healthcare needs.
TL;DR: In this paper, the authors present a comprehensive description of the trace element behaviour of apatite in various kinds of bedrocks (igneous rocks from felsic through to ultramafic compositions, metamorphic rocks from low to high grades and of diverse protolith composition, and authigenic apatites).
TL;DR: This new research is reviewed and the degree to which its findings support the key claims of predictive processing is evaluated, which has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap.
Abstract: For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long-standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP.
University of Zagreb1, University of Wolverhampton2, Leeds Beckett University3, Fordham University4, University of Malta5, Aalborg University6, Chapman University7, Teesside University8, Université du Québec en Outaouais9, University of Hong Kong10, University of Seville11, University College of Northern Denmark12, Beijing Normal University13, University of Sydney14, University College West15, Auckland University of Technology16, University of Auckland17, Queen's University Belfast18, University of Indianapolis19, Umeå University20, Victoria University, Australia21, University of Newcastle22, DePauw University23, Mzumbe University24, Mid Sweden University25, Dublin City University26, RMIT University27, University of Calgary28, London Metropolitan University29, University of South Carolina30, University of Split31, University of Lincoln32, University of Melbourne33, Community College of Philadelphia34, Global University (GU)35, University of Notre Dame Australia36, University of Latvia37, Tata Institute of Social Sciences38, University of Minnesota39, University of South Africa40, International Institute of Minnesota41, University of Waikato42, Northeast Normal University43, Curtin University44, University of Ibadan45, Adekunle Ajasin University46, Zhejiang Normal University47, National University of Ireland, Galway48
TL;DR: A collection of 84 author's testimonies and workspace photographs between 18 March and 5 May 2020 was published by as discussed by the authors, with the purpose of collecting the author's workspace photographs and their testimonies.
Abstract: A collection of 84 author's testimonies and workspace photographs between 18 March and 5 May 2020
16 Jan 2020
TL;DR: The proposed Improved WOA for Cloud task scheduling (IWC) has better convergence speed and accuracy in searching for the optimal task scheduling plans, compared to the current metaheuristic algorithms, and can also achieve better performance on system resource utilization.
Abstract: Task scheduling in cloud computing can directly affect the resource usage and operational cost of a system. To improve the efficiency of task executions in a cloud, various metaheuristic algorithms, as well as their variations, have been proposed to optimize the scheduling. In this article, for the first time, we apply the latest metaheuristics whale optimization algorithm (WOA) for cloud task scheduling with a multiobjective optimization model, aiming at improving the performance of a cloud system with given computing resources. On that basis, we propose an advanced approach called I mproved W OA for C loud task scheduling (IWC) to further improve the optimal solution search capability of the WOA-based method. We present the detailed implementation of IWC and our simulation-based experiments show that the proposed IWC has better convergence speed and accuracy in searching for the optimal task scheduling plans, compared to the current metaheuristic algorithms. Moreover, it can also achieve better performance on system resource utilization, in the presence of both small and large-scale tasks.
TL;DR: The window of opportunity presented through BCP self-assembly for nanomanufacturing is illustrated and the highlights discussed will aid in directing new research initiatives and facilitate the large-scale integration of BCP materials with broad societal impact.
TL;DR: In this paper, the authors investigated the changes in crystal lattice, phase, composition and lattice strain up to 1000°C using both in situ high temperature X-ray diffraction (XRD) and transmission electron microscopy (TEM).
TL;DR: In this review, recent progress and challenges on the functional inks and substrate materials for mass scale production and customization of printed flexible and wearable physiological signal monitoring sensor devices are summarized.
TL;DR: It is argued that cross-platform analysis addresses a gap in research methods in that it acknowledges the interplay between a social phenomenon under investigation and the medium within which it is being researched, thus illuminating the different affordances and cultures of web platforms.
Abstract: Analysis of social media using digital methods is a flourishing approach. However, the relatively easy availability of data collected via platform application programming interfaces has arguably le...
TL;DR: In this paper, the authors employ a VARMA DCC-GARCH model to search for portfolio diversification with Bitcoin in global industry portfolios and bond index, and find lower dynamic conditional correlations between Bitcoin and industry portfolios.
TL;DR: This paper examined the response of a broad set of digital assets to US Federal Fund interest rate and quantitative easing announcements, specifically examining associated volatility spillover and feedback effects, and classified each digital asset into one of three categories: Currencies; Protocols; and Decentralized Applications (dApps).
TL;DR: The state-of-the-art on adaptive 360° video delivery solutions considering end-to-end video streaming in general and then specifically of 360°video delivery are presented.
Abstract: Omnidirectional or 360° video is increasingly being used, mostly due to the latest advancements in immersive Virtual Reality (VR) technology. However, its wide adoption is hindered by the higher bandwidth and lower latency requirements than associated with traditional video content delivery. Diverse researchers propose and design solutions that help support an immersive visual experience of 360° video, primarily when delivered over a dynamic network environment. This paper presents the state-of-the-art on adaptive 360° video delivery solutions considering end-to-end video streaming in general and then specifically of 360° video delivery. Current and emerging solutions for adaptive 360° video streaming, including viewport-independent, viewport-dependent, and tile-based schemes are presented. Next, solutions for network-assisted unicast and multicast streaming of 360° video content are discussed. Different research challenges for both on-demand and live 360° video streaming are also analyzed. Several proposed standards and technologies and top international research projects are then presented. We demonstrate the ongoing standardization efforts for 360° media services that ensure interoperability and immersive media deployment on a massive scale. Finally, the paper concludes with a discussion about future research opportunities enabled by 360° video.
TL;DR: In this paper, the authors employ a multiple case study approach to investigate why multigenerational family firms innovate, drawing on the transgenerational entrepreneurship perspective, and find that the data collection process drew...
Abstract: Drawing on the transgenerational entrepreneurship perspective, we employ a multiple case study approach to investigate why multigenerational family firms innovate. The data collection process drew ...
TL;DR: This review focuses on immune checkpoint inhibitors - immunomodulatory agents that aim to relieve tumour-mediated immune-cell suppression that have shown impressive results in a range of solid cancers, particularly melanoma and non-small cell lung cancer.
TL;DR: In this article, the authors analyse the relationship between the price volatility of a broad range of cryptocurrencies and that of implied volatility of both United States and European financial markets as measured by the VIX and VSTOXX respectively.
TL;DR: In this article, the authors reported the detection of low-frequency radio emission from a quiescent star, GJ 1151, a member of the most common stellar type (red dwarf or spectral class M) in the Galaxy.
Abstract: Low-frequency (ν ≲ 150 MHz) stellar radio emission is expected to originate in the outer corona at heights comparable to and larger than the stellar radius. Such emission from the Sun has been used to study coronal structure, mass ejections and space-weather conditions around the planets1. Searches for low-frequency emission from other stars have detected only a single active flare star2 that is not representative of the wider stellar population. Here we report the detection of low-frequency radio emission from a quiescent star, GJ 1151—a member of the most common stellar type (red dwarf or spectral class M) in the Galaxy. The characteristics of the emission are similar to those of planetary auroral emissions3 (for example, Jupiter’s decametric emission), suggesting a coronal structure dominated by a global magnetosphere with low plasma density. Our results show that large-scale currents that power radio aurorae operate over a vast range of mass and atmospheric composition, ranging from terrestrial planets to main-sequence stars. The Poynting flux required to produce the observed radio emission cannot be generated by GJ 1151’s slow rotation, but can originate in a sub-Alfvenic interaction of its magnetospheric plasma with a short-period exoplanet. The emission properties are consistent with theoretical expectations4–7 for interaction with an Earth-size planet in an approximately one- to five-day-long orbit. Low-frequency radio emission from a normally quiescent M dwarf star suggests a radio aurora generated by the interaction between the stellar corona and an undetected Earth-sized planet.
TL;DR: A review of the current status of the energy conditions in general relativity and quantum field theory can be found in this paper, where the role of the equations of motion and the relation between classical and quantum theories are discussed.
Abstract: This review summarizes the current status of the energy conditions in general relativity and quantum field theory. We provide a historical review and a summary of technical results and applications, complemented with a few new derivations and discussions. We pay special attention to the role of the equations of motion and to the relation between classical and quantum theories. Pointwise energy conditions were first introduced as physically reasonable restrictions on matter in the context of general relativity. They aim to express e.g. the positivity of mass or the attractiveness of gravity. Perhaps more importantly, they have been used as assumptions in mathematical relativity to prove singularity theorems and the non-existence of wormholes and similar exotic phenomena. However, the delicate balance between conceptual simplicity, general validity and strong results has faced serious challenges, because all pointwise energy conditions are systematically violated by quantum fields and also by some rather simple classical fields. In response to these challenges, weaker statements were introduced, such as quantum energy inequalities and averaged energy conditions. These have a larger range of validity and may still suffice to prove at least some of the earlier results. One of these conditions, the achronal averaged null energy condition, has recently received increased attention. It is expected to be a universal property of the dynamics of all gravitating physical matter, even in the context of semiclassical or quantum gravity.
TL;DR: Pollen was the matrix most frequently evaluated in PPP studies and, of the compounds investigated, the majority were detected in pollen samples, and strong positive correlation was observed between neonicotinoid residues in pollen and nectar of cultivated plant species.
TL;DR: In this paper, a qualitative study of online student engagement experiences in a higher education institution is presented, focusing on the five central themes that make up the study's findings highlight key issues of students' sense of community, their support networks, balancing study with life, confidence, and their learning approaches.
Abstract: This article reports on a qualitative study which explored online student engagement experiences in a higher education institution. There are very few studies providing in-depth perspectives on the engagement experiences of online students. The project adopted a case study approach, following 24 online students over one academic year. The setting for the study was an undergraduate online Humanities programme at Dublin City University. The research question for the study was: What themes are central to online student engagement experiences? Data was collected from participant-generated learning portfolios and semi-structured interviews and analysed following a data-led thematic approach. The five central themes that make up the study’s findings highlight key issues of students’ sense of community, their support networks, balancing study with life, confidence, and their learning approaches. The findings of this study indicate that successful online student engagement was influenced by a number of psychosocial factors such as peer community, an engaging online teacher, and confidence and by structural factors such as lifeload and course design. One limitation of the study is that it is a relatively small, qualitative study, its findings provide insights into how online degrees can support online students to achieve successful and engaging learning experiences.