Describing long-term trends in precipitation using generalized additive models

With the current concern over climate change, descriptions of how rainfall patterns are changing over time can be useful. Observations of daily rainfall data over the last few decades provide information on these trends. Generalized linear models are typically used to model patterns in the occurrence and intensity of rainfall. These models describe rainfall patterns for an average year but are more limited when describing long-term trends, particularly when these are potentially non-linear. Generalized additive models (GAMS) provide a framework for modelling non-linear relationships by fitting smooth functions to the data. This paper describes how GAMS can extend the flexibility of models to describe seasonal patterns and long-term trends in the occurrence and intensity of daily rainfall using data from Mauritius from 1962 to 2001. Smoothed estimates from the models provide useful graphical descriptions of changing rainfall patterns over the last 40 years at this location. GAMS are particularly helpful when exploring non-linear relationships in the data. Care is needed to ensure the choice of smooth functions is appropriate for the data and modelling objectives. (c) 2008 Elsevier B.V. All rights reserved.

Nucleolin is regulated both at the level of transcription and translation

Nucleolin is a multi-functional protein that is located to the nucleolus. In tissue Culture cells, the stability of nucleolin is related to the proliferation status of the cell. During development, rat cardiomyocytes proliferate actively with increases in the mass of the heart being due to both hyperplasia and hypertrophy. The timing of this shift in the phenotype of the myocyte from one capable of undergoing hyperplasia to one that can grow only by hypertrophy occurs within 4 days of post-natal development. Thus, cardiomyocytes are an ideal model system in which to study the regulation of nucleolin during growth in vivo. Using Western blot and quantitative RT-PCR (TaqMan) we found that the amount of nucleolin is regulated both at the level of transcription and translation during the development of the cardiomyocyte. However, in cells which had exited the cell cycle and were subsequently given a hypertrophic stimulus, nucleolin was regulated post-transcriptionally. (c) 2005 Elsevier Inc. All rights reserved.

Calicivirus translation initiation requires an interaction between VPg and eIF4E

Unlike other positive-stranded RNA viruses that use either a 5'-cap structure or an internal ribosome entry site to direct translation of their messenger RNA, calicivirus translation is dependent on the presence of a protein covalently linked to the 50 end of the viral genome (VPg). We have shown a direct interaction of the calicivirus VPg with the cap-binding protein eIF4E. This interaction is required for calicivirus mRNA translation, as sequestration of eIF4E by 4E-BP1 inhibits translation. Functional analysis has shown that VPg does not interfere with the interaction between eIF4E and the cap structure or 4E-BP1, suggesting that VPg binds to eIF4E at a different site from both cap and 4E-BP1. This work lends support to the idea that calicivirus VPg acts as a novel 'cap substitute' during initiation of translation on virus mRNA.

Knowledge communication and translation- A knowledge transfer model

Purpose – The purpose of this paper is to propose a process model for knowledge transfer in using theories relating knowledge communication and knowledge translation. Design/methodology/approach – Most of what is put forward in this paper is based on a research project titled “Procurement for innovation and knowledge transfer (ProFIK)”. The project is funded by a UK government research council – The Engineering and Physical Sciences Research Council (EPSRC). The discussions are mainly grounded on a thorough review of literature accomplished as part of the research project. Findings – The process model developed in this paper has built upon the theory of knowledge transfer and the theory of communication. Knowledge transfer, per se, is not a mere transfer of knowledge. It involves different stages of knowledge transformation. Depending on the context of knowledge transfer, it can also be influenced by many factors; some positive and some negative. The developed model of knowledge transfer attempts to encapsulate all these issues in order to create a holistic framework. Originality/value of paper – An attempt has been made in the paper to combine some of the significant theories or findings relating to knowledge transfer together, making the paper an original and valuable one.

A family study of co-morbidity between generalized social phobia and generalized anxiety disorder in a non-clinic sample

Background: High rates of co-morbidity between Generalized Social Phobia (GSP) and Generalized Anxiety Disorder (GAD) have been documented. The reason for this is unclear. Family studies are one means of clarifying the nature of co-morbidity between two disorders. Methods: Six models of co-morbidity between GSP and GAD were investigated in a family aggregation study of 403 first-degree relatives of non-clinical probands: 37 with GSP, 22 with GAD, 15 with co-morbid GSP/GAD, and 41 controls with no history of GSP or GAD. Psychiatric data were collected for probands and relatives. Mixed methods (direct and family history interviews) were utilised. Results: Primary contrasts (against controls) found an increased rate of pure GSP in the relatives of both GSP probands and co-morbid GSP/GAD probands, and found relatives of co-morbid GSP/GAD probands to have an increased rate of both pure GAD and comorbid GSP/GAD. Secondary contrasts found (i) increased GSP in the relatives of GSP only probands compared to the relatives of GAD only probands; and (ii) increased GAD in the relatives of co-morbid GSP/GAD probands compared to the relatives of GSP only probands. Limitations: The study did not directly interview all relatives, although the reliability of family history data was assessed. The study was based on an all-female proband sample. The implications of both these limitations are discussed. Conclusions: The results were most consistent with a co-morbidity model indicating independent familial transmission of GSP and GAD. This has clinical implications for the treatment of patients with both disorders. (C) 2006 Elsevier B.V. All fights reserved.

Identification of nonlinear systems using generalized kernel models

Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an individually tuned diagonal covariance matrix that is determined by maximizing the correlation between the training data and the regressor using a repeated guided random search based on boosting optimization. An efficient construction algorithm based on orthogonal forward regression with leave-one-out (LOO) test statistic and local regularization (LR) is then used to select a parsimonious generalized kernel regression model from the resulting full regression matrix. The proposed modeling algorithm is fully automatic and the user is not required to specify any criterion to terminate the construction procedure. Experimental results involving two real data sets demonstrate the effectiveness of the proposed nonlinear system identification approach.