Institution
University of New Hampshire
Education•Durham, New Hampshire, United States•
About: University of New Hampshire is a education organization based out in Durham, New Hampshire, United States. It is known for research contribution in the topics: Population & Solar wind. The organization has 9379 authors who have published 24025 publications receiving 1020112 citations. The organization is also known as: UNH.
Topics: Population, Solar wind, Poison control, Magnetosphere, Heliosphere
Papers published on a yearly basis
Papers
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TL;DR: The results reveal both important differences and similarities between universities.
Abstract: This article presents rates of violence against dating partners by students at 31 universities in 16 countries (5 in Asia and the Middle East, 2 in Australia-New Zealand, 6 in Europe, 2 in Latin America, 16 in North America). Assault and injury rates are presented for males and females at each of the 31 universities. At the median university, 29% of the students physically assaulted a dating partner in the previous 12 months (range = 17% to 45%) and 7% had physically injured a partner (range = 2% to 20%). The results reveal both important differences and similarities between universities. Perhaps the most important similarity is the high rate of assault perpetrated by both male and female students in all the countries.
541 citations
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University of California1, University of Minnesota2, Centre national de la recherche scientifique3, University of Colorado Boulder4, Goddard Space Flight Center5, Swedish Institute of Space Physics6, Queen Mary University of London7, University of New Hampshire8, Imperial College London9, University of Maryland, College Park10, Johns Hopkins University Applied Physics Laboratory11, United States Naval Research Laboratory12, University of Michigan13, Southwest Research Institute14, University of Chicago15, Praxis16, University of California, Los Angeles17
TL;DR: The scientific objectives targeted by the SPP/FIELDS instrument, the instrument design itself, and the instrument concept of operations and planned data products are described.
Abstract: NASA’s Solar Probe Plus (SPP) mission will make the first in situ measurements of the solar corona and the birthplace of the solar wind. The FIELDS instrument suite on SPP will make direct measurements of electric and magnetic fields, the properties of in situ plasma waves, electron density and temperature profiles, and interplanetary radio emissions, amongst other things. Here, we describe the scientific objectives targeted by the SPP/FIELDS instrument, the instrument design itself, and the instrument concept of operations and planned data products.
540 citations
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University of Notre Dame1, Michigan State University2, University of New Hampshire3, University of Wyoming4, Oak Ridge National Laboratory5, University of Tennessee6, Marine Biological Laboratory7, Oregon State University8, University of Maryland, College Park9, University of New Mexico10, Kansas State University11, United States Department of Agriculture12, Montana State University13, Virginia Tech14, Central Washington University15, Ball State University16, Wright State University17, University of Georgia18, Indiana University19, University of Canterbury20, Arizona State University21, United States Geological Survey22, Washington State University Vancouver23
TL;DR: It is found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3−) concentrations, but that <1% of denitrified N is converted to N1O, and it is suggested that increased stream NO3− loading stimulatesDenitrification and concomitant N2o production, but does not increase the N2 O yield.
Abstract: Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N2O via microbial denitrification that converts N to N2O and dinitrogen (N2). The fraction of denitrified N that escapes as N2O rather than N2 (i.e., the N2O yield) is an important determinant of how much N2O is produced by river networks, but little is known about the N2O yield in flowing waters. Here, we present the results of whole-stream 15N-tracer additions conducted in 72 headwater streams draining multiple land-use types across the United States. We found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3−) concentrations, but that <1% of denitrified N is converted to N2O. Unlike some previous studies, we found no relationship between the N2O yield and stream water NO3−. We suggest that increased stream NO3− loading stimulates denitrification and concomitant N2O production, but does not increase the N2O yield. In our study, most streams were sources of N2O to the atmosphere and the highest emission rates were observed in streams draining urban basins. Using a global river network model, we estimate that microbial N transformations (e.g., denitrification and nitrification) convert at least 0.68 Tg·y−1 of anthropogenic N inputs to N2O in river networks, equivalent to 10% of the global anthropogenic N2O emission rate. This estimate of stream and river N2O emissions is three times greater than estimated by the Intergovernmental Panel on Climate Change.
536 citations
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University of California, Irvine1, University of Bristol2, British Geological Survey3, California Institute of Technology4, Alfred Wegener Institute for Polar and Marine Research5, University of Texas at Austin6, Aberystwyth University7, Scott Polar Research Institute8, Natural Environment Research Council9, Ohio State University10, Stockholm University11, Technical University of Denmark12, University of Ottawa13, University of Copenhagen14, University of New Hampshire15, Utrecht University16, Durham University17, University of Exeter18, Aarhus University19, University of Manitoba20, Imperial College London21, Woods Hole Oceanographic Institution22
TL;DR: A new compilation of Greenland bed topography that assimilates seafloor bathymetry and ice thickness data through a mass conservation approach is presented, yielding major improvements over previous data sets, particularly in the marine‐terminating sectors of northwest and southeast Greenland.
Abstract: Greenland's bed topography is a primary control on ice flow, grounding line migration, calving dynamics, and subglacial drainage. Moreover, fjord bathymetry regulates the penetration of warm Atlantic water (AW) that rapidly melts and undercuts Greenland's marine-terminating glaciers. Here we present a new compilation of Greenland bed topography that assimilates seafloor bathymetry and ice thickness data through a mass conservation approach. A new 150 m horizontal resolution bed topography/bathymetric map of Greenland is constructed with seamless transitions at the ice/ocean interface, yielding major improvements over previous data sets, particularly in the marine-terminating sectors of northwest and southeast Greenland. Our map reveals that the total sea level potential of the Greenland ice sheet is 7.42 ± 0.05 m, which is 7 cm greater than previous estimates. Furthermore, it explains recent calving front response of numerous outlet glaciers and reveals new pathways by which AW can access glaciers with marine-based basins, thereby highlighting sectors of Greenland that are most vulnerable to future oceanic forcing.
535 citations
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TL;DR: In this paper, the lognormal distribution is presented as a useful model for bio-optical variability at a variety of spatial and temporal scales, and a parametric statistical framework is presented for using the LDA model to assess the effects of heterogeneity and scale on closure.
Abstract: The lognormal distribution is presented as a useful model for bio-optical variability at a variety of spatial and temporal scales. A parametric statistical framework is presented for using the lognormal model to assess the effects of heterogeneity and scale on closure. Variability at small scales affects but is unresolved by large-scale measurements. An assumed lognormal distribution allows one to integrate over small-scale variability to predict large-scale measurements. Examples are presented to demonstrate how knowledge of the variance can be incorporated into models to relate measurements made at different scales.
534 citations
Authors
Showing all 9489 results
Name | H-index | Papers | Citations |
---|---|---|---|
Derek R. Lovley | 168 | 582 | 95315 |
Peter B. Reich | 159 | 790 | 110377 |
Jerry M. Melillo | 134 | 383 | 68894 |
Katja Klein | 129 | 1499 | 87817 |
David Finkelhor | 117 | 382 | 58094 |
Howard A. Stone | 114 | 1033 | 64855 |
James O. Hill | 113 | 532 | 69636 |
Tadayuki Takahashi | 112 | 932 | 57501 |
Howard Eichenbaum | 108 | 279 | 44172 |
John D. Aber | 107 | 204 | 48500 |
Andrew W. Strong | 99 | 563 | 42475 |
Charles T. Driscoll | 97 | 554 | 37355 |
Andrew D. Richardson | 94 | 282 | 32850 |
Colin A. Chapman | 92 | 491 | 28217 |
Nicholas W. Lukacs | 91 | 367 | 34057 |