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.

BIOTEX—Biosensing Textiles for Personalised Healthcare Management

Abstract: Textile-based sensors offer an unobtrusive method of continually monitoring physiological parameters during daily activities. Chemical analysis of body fluids, noninvasively, is a novel and exciting area of personalized wearable healthcare systems. BIOTEX was an EU-funded project that aimed to develop textile sensors to measure physiological parameters and the chemical composition of body fluids, with a particular interest in sweat. A wearable sensing system has been developed that integrates a textile-based fluid handling system for sample collection and transport with a number of sensors including sodium, conductivity, and pH sensors. Sensors for sweat rate, ECG, respiration, and blood oxygenation were also developed. For the first time, it has been possible to monitor a number of physiological parameters together with sweat composition in real time. This has been carried out via a network of wearable sensors distributed around the body of a subject user. This has huge implications for the field of sports and human performance and opens a whole new field of research in the clinical setting.

NanoECC: testing the limits of elliptic curve cryptography in sensor networks

Abstract: By using Elliptic Curve Cryptography (ECC), it has been recently shown that Public-Key Cryptography (PKC) is indeed feasible on resource-constrained nodes This feasibility, however, does not necessarily mean attractiveness, as the obtained results are still not satisfactory enough In this paper, we present results on implementing ECC, as well as the related emerging field of Pairing-Based Cryptography (PBC), on two of the most popular sensor nodes By doing that, we show that PKC is not only viable, but in fact attractive for WSNs As far as we know pairing computations presented in this paper are the most efficient results on the MICA2 (8-bit/73828-MHz ATmega128L) and Tmote Sky (16-bit/8192-MHz MSP-430) nodes

A supramolecular photocatalyst for the production of hydrogen and the selective hydrogenation of tolane.

Abstract: The central processes in natural photosynthesis are light-drivenelectrontransferfromthespecial-pairchromophoretothe primary acceptor, and the subsequent charge separationto enable the reduction of substrates. The transfer of thesedesign principles to artificial systems has led to the develop-ment of catalytic multicomponent systems for the photo-catalytic reduction of CO

Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis

Abstract: Weighted gene coexpression network analysis (WGCNA) is a powerful 'guilt-by-association'-based method to extract coexpressed groups of genes from large heterogeneous messenger RNA expression data sets. We have utilized WGCNA to identify 11 coregulated gene clusters across 2342 breast cancer samples from 13 microarray-based gene expression studies. A number of these transcriptional modules were found to be correlated to clinicopathological variables (e.g. tumor grade), survival endpoints for breast cancer as a whole (disease-free survival, distant disease-free survival and overall survival) and also its molecular subtypes (luminal A, luminal B, HER2+ and basal-like). Examples of findings arising from this work include the identification of a cluster of proliferation-related genes that when upregulated correlated to increased tumor grade and were associated with poor survival in general. The prognostic potential of novel genes, for example, ubiquitin-conjugating enzyme E2S (UBE2S) within this group was confirmed in an independent data set. In addition, gene clusters were also associated with survival for breast cancer molecular subtypes including a cluster of genes that was found to correlate with prognosis exclusively for basal-like breast cancer. The upregulation of several single genes within this coexpression cluster, for example, the potassium channel, subfamily K, member 5 (KCNK5) was associated with poor outcome for the basal-like molecular subtype. We have developed an online database to allow user-friendly access to the coexpression patterns and the survival analysis outputs uncovered in this study (available at http://glados.ucd.ie/Coexpression/).