Global ETD Search

241	e-Research and the Ubiquitious Open Grid Digital Libraries of the Future Patkar, Vivek, Chandra, Smita January 2006 (has links) Libraries have traditionally facilitated each of the following elements of research: production of new knowledge, its preservation and its organization to make it accessible for use over the generations. In modern times, the library is constantly required to meet the challenges of information explosion. Assimilating resources and restructuring practices to process the large data volumes both in the print and digital form held across the globe, therefore, becomes very important. A recourse by the libraries to application of successive forms of what can be called as Digital Library Technologies (DLT) has been the imperative. The Open Archives Initiative (OAI) is one recent development that is expected to assist the libraries to partner in setting up virtual learning environment and integrating research on a near universal scale. Future extension of this concept is envisaged to be that of Grid Computing. The technologies driving the â Gridâ would let people share computing power, databases, and other on-line tools securely across institutional and geographic boundaries without sacrificing the local autonomy. Ushering an era of the ubiquitous library helping the e-research is thus on the card. This paper reviews the emerging technological changes and charts the future role for the libraries with special reference to India. Virtual Communities Library Systems Archives Knowledge Organization Information Analysis Community Informatics Digital Libraries Internet Economics of Information Information Seeking Behaviors Knowledge Structures Electronic Publishing Wireless Technologies Information Extraction Geography Academic Libraries Social Informatics Information Ethics Knowledge Management Information Retrieval World Wide Web Digital Preservation Interdisciplinarity Learning Science User Studies Government Information Libraries Distributed Learning null Training Public Libraries Information Systems Information Literacy Geographic Digital Libraries Scholarly Communication Science Technology Studies Knowledge Representation
242	A dissection of class I phosphoinositide 3-kinase signalling in mouse embryonic fibroblasts and prostate organoids Sadiq, Barzan A. January 2018 (has links) Class I PI3Ks are a family (α, β, δ and γ) of ubiquitous lipid kinases that can be activated by cell surface receptors to 3-phosphorylate PI(4,5)P2 (phosphatidylinositol(4,5)-bisphosphate) and generate the signalling lipid PI(3,4,5)P3. The PI(3,4,5)P3 signal then activates a diverse collection of effector proteins involved in regulation of cell migration, metabolism and growth. The importance of this network is evidenced by the relatively high frequency with which cancers acquire gain-of-function mutations in this pathway and huge efforts to make PI3K inhibitors to treat cancer. The canonical model describing these events suggests class I PI3Ks are activated at the plasma membrane and generate PI(3,4,5)P3 in the inner leaflet of the plasma membrane where its effectors are activated. The PI(3,4,5)P3 signal can be terminated directly, by the tumour-suppressor and PI(3,4,5)P3-3-phosphatase PTEN, or modified to a distinct PI(3,4)P2 signal, by SHIP-family 5-phosphatases. The PI(3,4)P2 is removed by INPP4-family 4-phosphatases. Published work has shown that PI(3,4,5)P3 signalling can also occur in endosomes and nuclei, however, there is very little data defining the intracellular distribution of endogenous class I PI3Ks that supports these ideas; this is as a result of technical problems such as; their very low abundance, poor antibody-based tools and artefacts generated by overexpression of PI3Ks. Past work has indicated that, in PTEN-null mouse models of prostate tumour progression, either PI3Kβ or PI3Ks α and β, have important roles. Furthermore, the cell types and mechanism involved remained unclear. Recent published work in the host laboratory had indicated that there is an unexpectedly large accumulation of PI(3,4)P2 in PTEN-null cells that might be an important part of its status as a major tumour suppressor. The explanation and prevalence of this observation was unclear but potentially a result of PTEN also acting as a PI(3,4)P2 3-phosphatase in vivo. MEFs were derived from genetically-modified mice expressing endogenous, AviTagged class I PI3K subunits and used in experiments to define the subcellular localisation of class I PI3Ks. We found that following stimulation with PDGF, class IA PI3K subunits were unexpectedly depleted from the adherent basal membrane, in contrast, p85α and p110α, but not p85β and p110β, accumulated transiently in the nucleus. Interestingly, p110β, but none of the other subunits, was constitutively localised in the nucleus. These results support the idea that class I PI3K and PI(3,4,5)P3 signalling occurs in the nucleus. In organoids derived from WT, PI3Kγ-null or PTEN-null mouse prostate, application of PI3K-selective inhibitors revealed that PI3Kα had a dominant role in generating PI(3,4,5)P3 in prostate epithelial cells. The levels of PI(3,4)P2 were also elevated substantially in PTEN-null, compared to WT prostate organoids, use of PI3K-selective inhibitors suggested that it was also generated by PI3Kα. These data were consistent with the idea that PTEN can act as a PI(3,4)P2 3-phosphatase. Surprisingly, raising the pH of the organoids medium dramatically increased accumulation of PI(3,4,5)P3 and PI(3,4)P2, although the cause of this effect was unclear, we hypothesised the pH of the local environment may influence signalling via class I PI3Ks.
243	Statistical Inference Chou, Pei-Hsin 26 June 2008 (has links) In this paper, we will investigate the important properties of three major parts of statistical inference: point estimation, interval estimation and hypothesis testing. For point estimation, we consider the two methods of finding estimators: moment estimators and maximum likelihood estimators, and three methods of evaluating estimators: mean squared error, best unbiased estimators and sufficiency and unbiasedness. For interval estimation, we consider the the general confidence interval, confidence interval in one sample, confidence interval in two samples, sample sizes and finite population correction factors. In hypothesis testing, we consider the theory of testing of hypotheses, testing in one sample, testing in two samples, and the three methods of finding tests: uniformly most powerful test, likelihood ratio test and goodness of fit test. Many examples are used to illustrate their applications. finite population correction factor statistical hypothesis type I error composite hypothesis power Central limit theorem Basu theorem critical value goodness of fit test likelihood ratio test Lehmann-Scheffe theorem complete statistic ancillary statistic P-value type II error Rao-Blackwell theorem simple hypothesis one-sided test two-sided test significance level sufficient statistic alternative hypothesis testing hypothesis null hypothesis rejection region confidence interval confidence level minimum variance unbiased estimator interval estimation uniformly most powerful test Cramer-Rao inequality likelihood function mean square error moment estimator error of estimation point estimation maximum likelihood estimator bias consistent estimator minimal sufficient statistic factorization theorem unbiased estimator statistic most powerful test test statistics Neyman-Pearson lemma decision rule

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