On the search for spillovers from foreign direct investment (FDI) with spatial dependency

This paper examines various specifications that are used within the literature to test for spillovers from foreign direct investment (FDI). Analysis provides significant evidence of externalities from inward FDI, but it shows that these externalities are more localized than has previously been believed. Further, the results demonstrate that the econometric treatment of issues such as agglomeration, contiguity and spatial dependence significantly changes the conclusions regarding local and national spillovers from FDI, and productivity growth more generally.

Discriminative training of the hidden vector state model for semantic parsing

In this paper, we discuss how discriminative training can be applied to the hidden vector state (HVS) model in different task domains. The HVS model is a discrete hidden Markov model (HMM) in which each HMM state represents the state of a push-down automaton with a finite stack size. In previous applications, maximum-likelihood estimation (MLE) is used to derive the parameters of the HVS model. However, MLE makes a number of assumptions and unfortunately some of these assumptions do not hold. Discriminative training, without making such assumptions, can improve the performance of the HVS model by discriminating the correct hypothesis from the competing hypotheses. Experiments have been conducted in two domains: the travel domain for the semantic parsing task using the DARPA Communicator data and the Air Travel Information Services (ATIS) data and the bioinformatics domain for the information extraction task using the GENIA corpus. The results demonstrate modest improvements of the performance of the HVS model using discriminative training. In the travel domain, discriminative training of the HVS model gives a relative error reduction rate of 31 percent in F-measure when compared with MLE on the DARPA Communicator data and 9 percent on the ATIS data. In the bioinformatics domain, a relative error reduction rate of 4 percent in F-measure is achieved on the GENIA corpus.

Loss of Akt activity increases circulating soluble endoglin release in preeclampsia:identification of inter-dependency between Akt-1 and heme oxygenase-1

Aims - Endothelial dysfunction is a hallmark of preeclampsia. Desensitization of the phosphoinositide 3-kinase (PI3K)/Akt pathway underlies endothelial dysfunction and haeme oxygenase-1 (HO-1) is decreased in preeclampsia. To identify therapeutic targets, we sought to assess whether these two regulators act to suppress soluble endoglin (sEng), an antagonist of transforming growth factor-ß (TGF-ß) signalling, which is known to be elevated in preeclampsia. Methods and results - Vascular endothelial growth factor-A (VEGF-A), fibroblast growth factor (FGF-2), angiopoietin-1 (Ang-1), and insulin, which all activate the PI3K/Akt pathway, inhibited the release of sEng from endothelial cells. Inhibition of the PI3K/Akt pathway, by overexpression of phosphatase and tensin homolog (PTEN) or a dominant-negative isoform of Akt (Aktdn) induced sEng release from endothelial cells and prevented the inhibitory effect of VEGF-A. Conversely, overexpression of a constitutively active Akt (Aktmyr) inhibited PTEN and cytokine-induced sEng release. Systemic delivery of Aktmyr to mice significantly reduced circulating sEng, whereas Aktdn promoted sEng release. Phosphorylation of Akt was reduced in preeclamptic placenta and this correlated with the elevated level of circulating sEng. Knock-down of Akt using siRNA prevented HO-1-mediated inhibition of sEng release and reduced HO-1 expression. Furthermore, HO-1 null mice have reduced phosphorylated Akt in their organs and overexpression of Aktmyr failed to suppress the elevated levels of sEng detected in HO-1 null mice, indicating that HO-1 is required for the Akt-mediated inhibition of sEng. Conclusion - The loss of PI3K/Akt and/or HO-1 activity promotes sEng release and positive manipulation of these pathways offers a strategy to circumvent endothelial dysfunction.

Accountability changes in an NGO institutional and resource dependency perspectives on BRAC

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Parsing mathematical constructs:results from a preliminary eye tracking study

The semantic model described in this paper is based on ones developed for arithmetic (e.g. McCloskey et al. 1985, Cohene and Dehaene 1995), natural language processing (Fodor 1975, Chomsky 1981) and work by the author on how learners parse mathematical structures. The semantic model highlights the importance of the parsing process and the relationship between this process and the mathematical lexicon/grammar. It concludes by demonstrating that for a learner to become an efficient, competent mathematician a process of top-down parsing is essential.

Towards flexible parsing of structured textual model representations

Existing parsers for textual model representation formats such as XMI and HUTN are unforgiving and fail upon even the smallest inconsistency between the structure and naming of metamodel elements and the contents of serialised models. In this paper, we demonstrate how a fuzzy parsing approach can transparently and automatically resolve a number of these inconsistencies, and how it can eventually turn XML into a human-readable and editable textual model representation format for particular classes of models.