Relocation and investment in R&D by firms

The literature on foreign direct investment has analyzed corporate location decisions when firms invest in R&D to reduce production costs. Such firms may set up new plants in other developed countries while maintaining their domestic plants. In contrast, we here consider firms that close down their domestic operations and relocate to countries where wage costs are lower. Thus, we assume that firms may reduce their production costs by investing in R&D and likewise by moving their plants abroad. We show that these two mechanisms are complementary. When a firm relocates it invests more in R&D than when it does not change its location and, therefore, its production cost is lower in the first case. As a result, investment in R&D encourages firms to relocate.info:eu-repo/semantics/publishedVersio

Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information

Background : Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio case but also when homology information to known structures is available. Structural properties are also routinely used in protein analysis even when homology is available, largely because homology modelling is lower throughput than, say, secondary structure prediction. Nonetheless, predictors of secondary structure and solvent accessibility are virtually always ab initio. Results: Here we develop high-throughput machine learning systems for the prediction of protein secondary structure and solvent accessibility that exploit homology to proteins of known structure, where available, in the form of simple structural frequency profiles extracted from sets of PDB templates. We compare these systems to their state-of-the-art ab initio counterparts, and with a number of baselines in which secondary structures and solvent accessibilities are extracted directly from the templates. We show that structural information from templates greatly improves secondary structure and solvent accessibility prediction quality, and that, on average, the systems significantly enrich the information contained in the templates. For sequence similarity exceeding 30%, secondary structure prediction quality is approximately 90%, close to its theoretical maximum, and 2-class solvent accessibility roughly 85%. Gains are robust with respect to template selection noise, and significant for marginal sequence similarity and for short alignments, supporting the claim that these improved predictions may prove beneficial beyond the case in which clear homology is available. Conclusion: The predictive system are publicly available at the address http://distill.ucd.ieScience Foundation IrelandIrish Research Council for Science, Engineering and TechnologyHealth Research BoardUCD President's Award 2004au, da, ke, ab, sp - kpw30/11/1

Green Criminology Before ‘Green Criminology’: Amnesia and Absences

Although the first published use of the term ‘green criminology’ seems to have been made by Lynch (Green criminology. Aldershot, Hampshire, 1990/2006), elements of the analysis and critique represented by the term were established well before this date. There is much criminological engagement with, and analysis of, environmental crime and harm that occurred prior to 1990 that deserves acknowledgement. In this article, we try to illuminate some of the antecedents of green criminology. Proceeding in this way allows us to learn from ‘absences’, i.e. knowledge that existed but has been forgotten. We conclude by referring to green criminology not as an exclusionary label or barrier but as a symbol that guides and inspires the direction of research