15,909 research outputs found

    Productivity of Nanobiotechnology Research and Education in U.S. Universities

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    The National Science Foundation (NSF) estimates that nanotechnology will become a trillion-dollar industry by 2015 and that 800,000 workers will be needed in this field in the United States. Nanobiotechnology ― the interface of nanotechnology and the life sciences ― is one of the most active and promising application frontiers in nanotechnology. To assess the productivity of basic and applied research and education in this field, I construct a structural model composed of a system of three equations which respectively represent the productions of a university’s scientific publications, patents, and graduate training outputs. The model is estimated using a unique data set on thirty universities that participated in nanobiotechnology during the 1990-2005 period. Ten of them are private universities, ten are public land-grant universities, and ten are public non-land-grant universities. Universities indeed serve as a principal seedbed for future development of the cutting-edge nanobiotechnology. NSF investment in nanobiotechnology strongly affects the university’s basic science research and graduate education. The university’s research expenditures in life sciences, engineering, and physical sciences contribute to its nanobiotechnology fields. Importantly, there is no evidence that science and graduate training compete strongly with one another. Rather, basic science research and graduate education serve as strong complements to one another, while basic science and applied research, and applied research and graduate education serve as weak complements. On average, public non-land-grant universities are more efficient in applied research. Such characteristics of universities, however, do not significantly affect the universities’ efficiencies in basic research and graduate education in nanobiotechnology. Presence of a nanotechnology research center on campus enhances the university’s basic science research and a formal nanotechnology education program promotes the university’s graduate education.nanotechnology, graduate education, university research, productivity, Productivity Analysis, Research and Development/Tech Change/Emerging Technologies,

    UNIVERSITY BASIC RESEARCH AND APPLIED AGRICULTURAL BIOTECHNOLOGY

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    I examine the effects of R&D inputs on the subset of life-science outputs which demonstrably has influenced later technology, as evidenced by literature citations in agricultural biotechnology patents. Universities are found to be a principal seedbed for cutting-edge technology development. A university's life-science research budget strongly affects its technology-relevant life-science output as well as graduate education.Research and Development/Tech Change/Emerging Technologies,

    Hypothesis Testing of Matrix Graph Model with Application to Brain Connectivity Analysis

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    Brain connectivity analysis is now at the foreground of neuroscience research. A connectivity network is characterized by a graph, where nodes represent neural elements such as neurons and brain regions, and links represent statistical dependences that are often encoded in terms of partial correlations. Such a graph is inferred from matrix-valued neuroimaging data such as electroencephalography and functional magnetic resonance imaging. There have been a good number of successful proposals for sparse precision matrix estimation under normal or matrix normal distribution; however, this family of solutions do not offer a statistical significance quantification for the estimated links. In this article, we adopt a matrix normal distribution framework and formulate the brain connectivity analysis as a precision matrix hypothesis testing problem. Based on the separable spatial-temporal dependence structure, we develop oracle and data-driven procedures to test the global hypothesis that all spatial locations are conditionally independent, which are shown to be particularly powerful against the sparse alternatives. In addition, simultaneous tests for identifying conditional dependent spatial locations with false discovery rate control are proposed in both oracle and data-driven settings. Theoretical results show that the data-driven procedures perform asymptotically as well as the oracle procedures and enjoy certain optimality properties. The empirical finite-sample performance of the proposed tests is studied via simulations, and the new tests are applied on a real electroencephalography data analysis

    ARE BASIC SCIENCE AND BIOTECHNOLOGY COMPLEMENTARY ACTIVITIES?

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    Enhancing agricultural productivity depends greatly on the management of information flows between basic and applied research. A framework is developed to examine the mutual relationship between molecular biological research and agricultural biotechnology innovations. Preliminary results provide a basis for university decision-making in both the short and long run.Research and Development/Tech Change/Emerging Technologies,
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