Dublin City University

About: Dublin City University is a education organization based out in Dublin, Ireland. It is known for research contribution in the topics: Machine translation & Laser. The organization has 5904 authors who have published 17178 publications receiving 389376 citations. The organization is also known as: National Institute for Higher Education, Dublin & DCU.

Cooperative Organization in Iron Oxide Multi-Core Nanoparticles Potentiates Their Efficiency as Heating Mediators and MRI Contrast Agents

Abstract: In the pursuit of optimized magnetic nanostructures for diagnostic and therapeutic applications, the role of nanoparticle architecture has been poorly investigated. In this study, we demonstrate that the internal collective organization of multi-core iron oxide nanoparticles can modulate their magnetic properties in such a way as to critically enhance their hyperthermic efficiency and their MRI T1 and T2 contrast effect. Multi-core nanoparticles composed of maghemite cores were synthesized through a polyol approach, and subsequent electrostatic colloidal sorting was used to fractionate the suspensions by size and hence magnetic properties. We obtained stable suspensions of citrate-stabilized nanostructures ranging from single-core 10 nm nanoparticles to multi-core magnetically cooperative 30 nm nanoparticles. Three-dimensional oriented attachment of primary cores results in enhanced magnetic susceptibility and decreased surface disorder compared to individual cores, while preserving a superparamagnetic-li...

Exercise intensity-dependent regulation of peroxisome proliferator-activated receptor coactivator-1 mRNA abundance is associated with differential activation of upstream signalling kinases in human skeletal muscle.

Abstract: Skeletal muscle contraction increases intracellular ATP turnover, calcium flux, and mechanical stress, initiating signal transduction pathways that modulate peroxisome proliferator-activated receptor gamma coactivator-1alpha (PGC-1alpha)-dependent transcriptional programmes. The purpose of this study was to determine if the intensity of exercise regulates PGC-1alpha expression in human skeletal muscle, coincident with activation of signalling cascades known to regulate PGC-1alpha transcription. Eight sedentary males expended 400 kcal (1674 kj) during a single bout of cycle ergometer exercise on two separate occasions at either 40% (LO) or 80% (HI) of . Skeletal muscle biopsies from the m. vastus lateralis were taken at rest and at +0, +3 and +19 h after exercise. Energy expenditure during exercise was similar between trials, but the high intensity bout was shorter in duration (LO, 69.9 +/- 4.0 min; HI, 36.0 +/- 2.2 min, P < 0.05) and had a higher rate of glycogen utilization (P < 0.05). PGC-1alpha mRNA abundance increased in an intensity-dependent manner +3 h after exercise (LO, 3.8-fold; HI, 10.2-fold, P < 0.05). AMP-activated protein kinase (AMPK) (2.8-fold, P < 0.05) and calcium/calmodulin-dependent protein kinase II (CaMKII) phosphorylation (84%, P < 0.05) increased immediately after HI but not LO. p38 mitogen-activated protein kinase (MAPK) phosphorylation increased after both trials (2.0-fold, P < 0.05), but phosphorylation of the downstream transcription factor, activating transcription factor-2 (ATF-2), increased only after HI (2.4-fold, P < 0.05). Cyclic-AMP response element binding protein (CREB) phosphorylation was elevated at +3 h after both trials (80%, P < 0.05) and class IIa histone deacetylase (HDAC) phosphorylation increased only after HI (2.0-fold, P < 0.05). In conclusion, exercise intensity regulates PGC-1alpha mRNA abundance in human skeletal muscle in response to a single bout of exercise. This effect is mediated by differential activation of multiple signalling pathways, with ATF-2 and HDAC phosphorylation proposed as key intensity-dependent mediators.

Cloud Migration Research: A Systematic Review

Abstract: Background--By leveraging cloud services, organizations can deploy their software systems over a pool of resources. However, organizations heavily depend on their business-critical systems, which have been developed over long periods. These legacy applications are usually deployed on-premise. In recent years, research in cloud migration has been carried out. However, there is no secondary study to consolidate this research. Objective--This paper aims to identify, taxonomically classify, and systematically compare existing research on cloud migration. Method--We conducted a systematic literature review (SLR) of 23 selected studies, published from 2010 to 2013. We classified and compared the selected studies based on a characterization framework that we also introduce in this paper. Results--The research synthesis results in a knowledge base of current solutions for legacy-to-cloud migration. This review also identifies research gaps and directions for future research. Conclusion--This review reveals that cloud migration research is still in early stages of maturity, but is advancing. It identifies the needs for a migration framework to help improving the maturity level and consequently trust into cloud migration. This review shows a lack of tool support to automate migration tasks. This study also identifies needs for architectural adaptation and self-adaptive cloud-enabled systems.

Terms in context

Abstract: Terms in Context applies the methodology that has been developed over the last two decades in corpus linguistics to the relatively new and still little developed field of corpus-based terminography. While corpora are already being used by some terminologists for the identification of terms and retrieval of contextual fragments, this book describes the first attempt to use corpora for terminography in much the same way as large general reference corpora are already being used for general language lexicography. The author goes beyond the standard problem of identifying terms as opposed to non-terminological lexical items in text and focuses on identifying metalanguage patterns which point to the presence in text of (parts of) reusable definitions of terms. The author examines these patterns and shows how the information which they contain can be retrieved and used as input for terminological entries. Terms in Context should be of interest to ‘traditional’ terminologists who have not previously considered adopting a corpus-based approach to their work or at least not on the scale proposed here; to ‘modern’ terminologists who use text primarily for the identification of terms and the retrieval of contextual examples; to those in the corpus linguistic community who have hitherto used general language corpora for the purposes of lexicography and have not previously considered using special purpose corpora for more specific lexicography studies; and to academics in the ESP/LSP community who are interested in showing students how to use text as a means of ascertaining the meaning of terms.

Datestamping the Bitcoin and Ethereum Bubbles

Abstract: We examine the existence and dates of pricing bubbles in Bitcoin and Ethereum, two popular cryptocurrencies using the Phillips et al. (2011) methodology. In contrast to previous papers, we examine the fundamental drivers of the price. Having derived ratios that are economically and computationally sensible, we use these variables to detect and datestamp bubbles. Our conclusion is that there are periods of clear bubble behaviour, with Bitcoin now almost certainly in a bubble phase.