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Institution

Michigan State University

EducationEast Lansing, Michigan, United States
About: Michigan State University is a education organization based out in East Lansing, Michigan, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 60109 authors who have published 137074 publications receiving 5633022 citations. The organization is also known as: MSU & Michigan State.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a similarity transform was used to reduce the Navier-Stokes equations to a set of non-linear ordinary differential equations, which are then integrated numerically.
Abstract: The stagnation flow towards a shrinking sheet is studied. A similarity transform reduces the Navier–Stokes equations to a set of non-linear ordinary differential equations which are then integrated numerically. Both two-dimensional and axisymmetric stagnation flows are considered. It is found that solutions do not exist for larger shrinking rates and may be non-unique in the two-dimensional case. The non-alignment of the stagnation flow and the shrinking sheet complicates the flow structure. Convective heat transfer decreases with the shrinking rate due to an increase in boundary layer thickness.

610 citations

Journal ArticleDOI
TL;DR: The RBD scale is demonstrated to have a high degree of content, construct, and predictive validity and offers guidance to practitioners on how to develop the best persuasive message possible to motivate healthy behaviors.
Abstract: The goal of this study was to develop and validate the Risk Behavior Diagnosis (RBD) Scale for use by health care providers and practitioners interested in promoting healthy behaviors. Theoreticall...

610 citations

Journal ArticleDOI
TL;DR: Accuracy of estimating the stage of an estrous cycle by appearance of corpora lutea was determined in a double-blind study that observed estrus in a group of heifers and estimated stage of the estrus by visual inspection of their corporaLutea.

609 citations

Journal ArticleDOI
27 Apr 2007-Science
TL;DR: An overview of various classes of nanostructured materials is provided and it is suggested that successful solutions to these nanostructure problems will involve interactions among researchers from materials science, physics, chemistry, computer science, and applied mathematics, working within a “complex modeling” paradigm.
Abstract: Emerging complex functional materials often have atomic order limited to the nanoscale. Examples include nanoparticles, species encapsulated in mesoporous hosts, and bulk crystals with intrinsic nanoscale order. The powerful methods that we have for solving the atomic structure of bulk crystals fail for such materials. Currently, no broadly applicable, quantitative, and robust methods exist to replace crystallography at the nanoscale. We provide an overview of various classes of nanostructured materials and review the methods that are currently used to study their structure. We suggest that successful solutions to these nanostructure problems will involve interactions among researchers from materials science, physics, chemistry, computer science, and applied mathematics, working within a "complex modeling" paradigm that combines theory and experiment in a self-consistent computational framework.

609 citations

Journal ArticleDOI
TL;DR: Ingestion of these components has effect on diverse physiological processes impacting normal health and chronic disease, such as the regulation of plasma lipid levels, cardiovascular function, and neuronal development and visual function.

608 citations


Authors

Showing all 60636 results

NameH-indexPapersCitations
David Miller2032573204840
Anil K. Jain1831016192151
D. M. Strom1763167194314
Feng Zhang1721278181865
Derek R. Lovley16858295315
Donald G. Truhlar1651518157965
Donald E. Ingber164610100682
J. E. Brau1621949157675
Murray F. Brennan16192597087
Peter B. Reich159790110377
Wei Li1581855124748
Timothy C. Beers156934102581
Claude Bouchard1531076115307
Mercouri G. Kanatzidis1521854113022
James J. Collins15166989476
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023250
2022752
20217,041
20206,870
20196,548
20185,779