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Institution

Michigan Technological University

EducationHoughton, Michigan, United States
About: Michigan Technological University is a education organization based out in Houghton, Michigan, United States. It is known for research contribution in the topics: Population & Volcano. The organization has 8023 authors who have published 17422 publications receiving 481780 citations. The organization is also known as: MTU & Michigan Tech.


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Journal ArticleDOI
TL;DR: It is found that these BNNTs have an absorption band edge of 5.9 eV, approaching that of single h-BN crystals, which is promising for future nanoscale deep-UV light emitting devices.
Abstract: Effective growth of multiwalled boron nitride nanotubes (BNNTs) has been obtained by thermal chemical vapor deposition (CVD). This is achieved by a growth vapor trapping approach as guided by the theory of nucleation. Our results enable the growth of BNNTs in a conventional horizontal tube furnace within an hour at 1200 °C. We found that these BNNTs have an absorption band edge of 5.9 eV, approaching that of single h-BN crystals, which are promising for future nanoscale deep-UV light emitting devices.

192 citations

Journal ArticleDOI
Benjamin W. Abbott1, Jeremy B. Jones1, Edward A. G. Schuur2, F. Stuart Chapin1, William B. Bowden3, M. Syndonia Bret-Harte1, Howard E. Epstein4, Mike D. Flannigan5, Tamara K. Harms1, Teresa N. Hollingsworth6, Michelle C. Mack2, A. David McGuire7, Susan M. Natali8, Adrian V. Rocha9, Suzanne E. Tank5, Merritt R. Turetsky10, Jorien E. Vonk11, Kimberly P. Wickland7, George R. Aiken7, Heather D. Alexander12, Rainer M. W. Amon13, Brian W. Benscoter14, Yves Bergeron15, Kevin Bishop16, Olivier Blarquez17, Ben Bond-Lamberty18, Amy L. Breen1, Ishi Buffam19, Yihua Cai20, Christopher Carcaillet21, Sean K. Carey22, Jing M. Chen23, Han Y. H. Chen24, Torben R. Christensen25, Lee W. Cooper26, J. Hans C. Cornelissen11, William J. de Groot27, Thomas H. DeLuca28, Ellen Dorrepaal29, Ned Fetcher30, Jacques C. Finlay31, Bruce C. Forbes, Nancy H. F. French32, Sylvie Gauthier27, Martin P. Girardin27, Scott J. Goetz8, Johann G. Goldammer33, Laura Gough34, Paul Grogan35, Laodong Guo36, Philip E. Higuera37, Larry D. Hinzman1, Feng Sheng Hu38, Gustaf Hugelius39, Elchin Jafarov40, Randi Jandt1, Jill F. Johnstone41, Jan Karlsson29, Eric S. Kasischke, Gerhard Kattner42, Ryan C. Kelly, Frida Keuper43, George W. Kling44, Pirkko Kortelainen45, Jari Kouki46, Peter Kuhry39, Hjalmar Laudon16, Isabelle Laurion15, Robie W. Macdonald47, Paul J. Mann48, Pertti J. Martikainen46, James W. McClelland49, Ulf Molau50, Steven F. Oberbauer14, David Olefeldt5, David Paré27, Marc-André Parisien27, Serge Payette51, Changhui Peng52, Oleg S. Pokrovsky53, Edward B. Rastetter54, Peter A. Raymond55, Martha K. Raynolds1, Guillermo Rein56, James F. Reynolds57, Martin D. Robards, Brendan M. Rogers8, Christina Schaedel2, Kevin Schaefer40, Inger Kappel Schmidt58, Anatoly Shvidenko, Jasper Sky, Robert G. M. Spencer14, Gregory Starr59, Robert G. Striegl7, Roman Teisserenc60, Lars J. Tranvik61, Tarmo Virtanen, Jeffrey M. Welker62, Sergei Zimov63 
University of Alaska Fairbanks1, Northern Arizona University2, University of Vermont3, University of Virginia4, University of Alberta5, United States Department of Agriculture6, United States Geological Survey7, Woods Hole Oceanographic Institution8, University of Notre Dame9, University of Guelph10, VU University Amsterdam11, Mississippi State University12, University of North Texas13, Florida State University14, Université du Québec15, Swedish University of Agricultural Sciences16, McGill University17, United States Department of Energy18, University of Cincinnati19, Xiamen University20, École Normale Supérieure21, McMaster University22, University of Toronto23, Lakehead University24, Aarhus University25, University of Maryland Center for Environmental Science26, Natural Resources Canada27, University of Washington28, Umeå University29, Wilkes University30, University of Minnesota31, Michigan Technological University32, Max Planck Society33, University System of Maryland34, Queen's University35, University of Wisconsin–Milwaukee36, University of Montana System37, University of Illinois at Chicago38, Stockholm University39, University of Colorado Boulder40, University of Saskatchewan41, Alfred Wegener Institute for Polar and Marine Research42, Institut national de la recherche agronomique43, University of Michigan44, Finnish Environment Institute45, University of Eastern Finland46, Fisheries and Oceans Canada47, Northumbria University48, University of Texas at Austin49, University of Gothenburg50, Laval University51, Northwest A&F University52, Tomsk State University53, Marine Biological Laboratory54, Yale University55, Imperial College London56, Duke University57, University of Copenhagen58, University of Alabama59, Centre national de la recherche scientifique60, Uppsala University61, University of Alaska Anchorage62, Russian Academy of Sciences63
TL;DR: As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export as mentioned in this paper, and models predict that some portion of this release w...
Abstract: As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release w ...

192 citations

Journal ArticleDOI
TL;DR: It is demonstrated that ZIF-8's C(ij)'s can be reliably predicted, and its elastic deformation mechanism is linked to the pliant ZnN(4) tetrahedra, which is the lowest yet reported for a single-crystalline extended solid.
Abstract: Using Brillouin scattering, we measured the single-crystal elastic constants (C(ij)'s) of a prototypical metal-organic framework (MOF): zeolitic imidazolate framework (ZIF)-8 [Zn(2-methylimidazolate)(2)], which adopts a zeolitic sodalite topology and exhibits large porosity. Its C(ij)'s under ambient conditions are (in GPa) C(11)=9.522(7), C(12)=6.865(14), and C(44)=0.967(4). Tensorial analysis of the C(ij)'s reveals the complete picture of the anisotropic elasticity in cubic ZIF-8. We show that ZIF-8 has a remarkably low shear modulus G(min) < or approximately 1 GPa, which is the lowest yet reported for a single-crystalline extended solid. Using ab initio calculations, we demonstrate that ZIF-8's C(ij)'s can be reliably predicted, and its elastic deformation mechanism is linked to the pliant ZnN(4) tetrahedra. Our results shed new light on the role of elastic constants in establishing the structural stability of MOF materials and thus their suitability for practical applications.

191 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a framework that uses trademarks as measures of firms' branding efforts and propose that they are indicators of firm efforts to build brand awareness and associations among consumers.
Abstract: Firms spend considerable efforts to build brand awareness and associations among consumers. Yet there is a limited understanding of the financial returns of such investments. In this article, the authors present a framework that uses trademarks as measures of firms' branding efforts. They classify trademarks into two categories—brand-identification trademarks and brand-association trademarks—and propose that they are indicators of firm efforts to build brand awareness and associations among consumers, respectively. The authors then evaluate the chain of effects linking such assets with metrics of firms' financial value. A longitudinal analysis of data collected from secondary sources reveals that the stock (i.e., total number) of brand-association trademarks available to firms in time period t increases their cash flow, Tobin's q, return on assets, and stock returns and reduces their cash-flow variability in period t + 1. Furthermore, the authors observe that the stock of brand-identification tra...

191 citations

Journal ArticleDOI
TL;DR: The extent to which Ne/N is depressed by FPS over the range of fluctuations observed in wild animal populations is considered, and a method for predicting Ne/n from a standard measure of population variability is presented, and the implications of this theoretical relationship are discussed.
Abstract: The effective size of a population (Ne) quantifies the rate at which genetic diversity is eroded by genetic drift (i.e., 112Ne per generation), a fundamental process of evolutionary change. Genetic diversity and its rate of decay have been linked with key components of population fitness (Allendorf and Leary 1987; Ralls et al. 1988; Briscoe et al. 1992; Newman and Pilson 1997; but see Britten 1996). Ne is thus a central parameter both in studies aimed at understanding evolution (Falconer and Mackay 1996) and in the field of conservation genetics (Lande and Barrowclough 1987; Nunney and Campbell 1993; Nunney and Elam 1994). Unfortunately, accounting for all factors that influence Ne is notoriously difficult (reviewed by Caballero 1994). This difficulty is apparently responsible for significant disagreement between theoretical (Nunney 1993) and observed values of the ratio, Ne/N (Frankham 1995). Here we investigate whether this disagreement can be reconciled by incorporating the effect of a factor long known to reduce Ne, namely temporal fluctuations in population size (FPS; Wright 1938). More specifically, we consider the extent to which Ne/N is depressed by FPS over the range of fluctuations observed in wild animal populations. In addition, we present a method for predicting Ne/N from a standard measure of population variability, and we discuss the implications of this theoretical relationship. Several factors affect the effective size of a population: fluctuations in size, variance in fecundity, sex ratio, and the degree to which generations overlap (Crow and Kimura 1970). One difficulty in estimating Ne is that no single formula simultaneously accounts for all these factors. This difficulty would be largely inconsequential if the ratio Ne/N were known to fall consistently within a narrow range. Estimating Ne would be trivial because N is often relatively easily estimated. Theoretical and empirical studies have searched for such a range of Ne/N. Theoretical studies have explored the plausible range of Ne/N through analysis of a reparameterized version of Hill's (1972) expression for Ne (Nunney 1991, 1993, 1996). This reparameterization provides several advantages. Ne is expressed in parameters that are biologically interpretable, and for which typical ranges are known. In addition, the parameters can be estimated from data commonly available from single-season studies of real populations (Nunney and Elam 1994). Through thorough numerical exploration of the parameter space, these studies led to the conclusion that Ne/N is usually close to 0.5 and only rarely outside the range 0.250.75 (Nunney 1991, 1993, 1996; hereafter, referred to as the theoretical expectation.) In contrast with this theoretical expectation, a review of 192 empirical estimates (based on a variety of demographic and genetic methods) revealed that Ne/N was usually less than 0.5 (Frankham 1995; hereafter, referred to as empirical estimates.) In fact, approximately one-third of the Ne/N estimates were less than 0.25, and a subset of these estimates (37 from animal taxa) accounting for all factors that influence Ne had an average Ne/N of 0.15 (median = 0.08). By contrast, a subset of estimates (27 from animal taxa) accounting for all factors except FPS had an average Ne/N of 0.38 (median = 0.38). The discrepancy between theoretical expectation and empirical estimates may thus be largely attributable to the fact that the theoretical expectation is based on the assumption of constant N. The theoretical expectation may provide a reasonable estimate of the short-term Ne/N, but the longerterm ratio may often be less than 0.25, owing to the effect of FPS. A long-term estimate of Ne that accounts for FPS is obtained by transforming a series of short-term effective sizes (Wright 1938; see also Crow and Kimura 1970; Lande and Barrowclough 1987):

190 citations


Authors

Showing all 8104 results

NameH-indexPapersCitations
Anil K. Jain1831016192151
Marc W. Kirschner162457102145
Yonggang Huang13679769290
Hong Wang110163351811
Fei Wang107182453587
Emanuele Bonamente10521940826
Haoshen Zhou10451937609
Nicholas J. Turro104113153827
Yang Shao-Horn10245849463
Richard P. Novick9929534542
Markus J. Buehler9560933054
Martin L. Yarmush9170234591
Alan Robock9034627022
Patrick M. Schlievert9044432037
Lonnie O. Ingram8831622217
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202349
2022154
2021882
2020891
2019892
2018893