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: Context (language use) & Machine translation. 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.

Ionogel-based light-actuated valves for controlling liquid flow in micro-fluidic manifolds

Abstract: We present the fabrication, characterisation and performance of four novel ionic liquid polymer gels (ionogels) as photo-actuated valves incorporated into micro-fluidic manifolds. The ionogels incorporate benzospiropyran units and phosphonium-based ionic liquids. Each ionogel is photo-polymerised in situ in the channels of a poly(methyl methacrylate) micro-fluidic device, generating a manifold incorporating four different micro-valves. The valves are actuated by simply applying localised white light irradiation, meaning that no physical contact between the actuation impulse (light) and the valve structure is required. Through variation of the composition of the ionogels, each of the micro-valves can be tuned to open at different times under similar illumination conditions. Therefore, flows through the manifold can be independently controlled by a single light source. At present, the contraction process to open the channel is relatively rapid (seconds) while the recovery (expansion) process to re-close the channel is relatively slow (minutes), meaning that the valve, in its current form, is better suited for single-actuation events.

Topic-dependent sentiment analysis of financial blogs

Abstract: While most work in sentiment analysis in the financial domain has focused on the use of content from traditional finance news, in this work we concentrate on more subjective sources of information, blogs. We aim to automatically determine the sentiment of financial bloggers towards companies and their stocks. To do this we develop a corpus of financial blogs, annotated with polarity of sentiment with respect to a number of companies. We conduct an analysis of the annotated corpus, from which we show there is a significant level of topic shift within this collection, and also illustrate the difficulty that human annotators have when annotating certain sentiment categories. To deal with the problem of topic shift within blog articles, we propose text extraction techniques to create topic-specific sub-documents, which we use to train a sentiment classifier. We show that such approaches provide a substantial improvement over full documentclassification and that word-based approaches perform better than sentence-based or paragraph-based approaches.

European Trade Credit Use and Firm Survival

Abstract: This paper examines the role of trade credit in a comprehensive panel of 290,301 SMEs across 15 European countries over the period 2003-2012. The results show that trade credit served as an important source of finance for credit constrained firms, and that the financial position of firms entering the crisis was the main determinant of trade credit use over the financial crisis period. Evidence supporting a significant redistribution effect is reported with cash rich firms extending up to 9 times more net trade credit than their less financially resourced counterparts. Country factors, including banking concentration and the strength of institutional and creditor rights are reported as significant determinants of trade credit use. Distinctively, the paper shows that trade credit significantly reduced the likelihood of firm financial distress and failure. The results are robust to several econometric concerns, including endogeneity arising from possible omitted variables.