University of Maine
Education•Orono, Maine, United States•
About: University of Maine is a(n) education organization based out in Orono, Maine, United States. It is known for research contribution in the topic(s): Population & Ice sheet. The organization has 8637 authors who have published 16932 publication(s) receiving 590124 citation(s). The organization is also known as: University of Maine at Orono.
Topics: Population, Ice sheet, Glacial period, Glacier, Ice core
Papers published on a yearly basis
University of California, San Diego1, Smithsonian Tropical Research Institute2, State Street Corporation3, University of Florida4, University of California, Davis5, Bates College6, Australian National University7, University of Oregon8, University of California, Santa Cruz9, James Cook University10, University of Chicago11, University of North Carolina at Chapel Hill12, National Museum of Natural History13, University of Maine14, University of California, Santa Barbara15
TL;DR: Paleoecological, archaeological, and historical data show that time lags of decades to centuries occurred between the onset of overfishing and consequent changes in ecological communities, because unfished species of similar trophic level assumed the ecological roles of over-fished species until they too were overfished or died of epidemic diseases related to overcrowding as mentioned in this paper.
Abstract: Ecological extinction caused by overfishing precedes all other pervasive human disturbance to coastal ecosystems, including pollution, degradation of water quality, and anthropogenic climate change. Historical abundances of large consumer species were fantastically large in comparison with recent observations. Paleoecological, archaeological, and historical data show that time lags of decades to centuries occurred between the onset of overfishing and consequent changes in ecological communities, because unfished species of similar trophic level assumed the ecological roles of overfished species until they too were overfished or died of epidemic diseases related to overcrowding. Retrospective data not only help to clarify underlying causes and rates of ecological change, but they also demonstrate achievable goals for restoration and management of coastal ecosystems that could not even be contemplated based on the limited perspective of recent observations alone.
State Street Corporation1, University of California, Santa Barbara2, University of Hawaii at Manoa3, Stanford University4, Wildlife Conservation Society5, Arizona State University6, University of North Carolina at Chapel Hill7, National Oceanic and Atmospheric Administration8, Environmental Defense Fund9, Ocean Conservancy10, The Nature Conservancy11, University of Maine12, University of British Columbia13
TL;DR: This article developed an ecosystem-specific, multiscale spatial model to synthesize 17 global data sets of anthropogenic drivers of ecological change for 20 marine ecosystems and found that no area is unaffected by human influence and that a large fraction (41%) is strongly affected by multiple drivers.
Abstract: The management and conservation of the world's oceans require synthesis of spatial data on the distribution and intensity of human activities and the overlap of their impacts on marine ecosystems. We developed an ecosystem-specific, multiscale spatial model to synthesize 17 global data sets of anthropogenic drivers of ecological change for 20 marine ecosystems. Our analysis indicates that no area is unaffected by human influence and that a large fraction (41%) is strongly affected by multiple drivers. However, large areas of relatively little human impact remain, particularly near the poles. The analytical process and resulting maps provide flexible tools for regional and global efforts to allocate conservation resources; to implement ecosystem-based management; and to inform marine spatial planning, education, and basic research.
TL;DR: The analysis supports theory claiming that calls to increase the number of students receiving STEM degrees could be answered, at least in part, by abandoning traditional lecturing in favor of active learning and supports active learning as the preferred, empirically validated teaching practice in regular classrooms.
Abstract: creased by 0.47 SDs under active learning (n = 158 studies), and that the odds ratio for failing was 1.95 under traditional lecturing (n = 67 studies). These results indicate that average examination scores improved by about 6% in active learning sections, and that students in classes with traditional lecturing were 1.5 times more likely to fail than were students in classes with active learning. Heterogeneity analyses indicated that both results hold across the STEM disciplines, that active learning increases scores on concept inventories more than on course examinations, and that active learning appears effective across all class sizes—although the greatest effects are in small (n ≤ 50) classes. Trim and fill analyses and fail-safe n calculations suggest that the results are not due to publication bias. The results also appear robust to variation in the methodological rigor of the included studies, based on the quality of controls over student quality and instructor identity. This is the largest and most comprehensive metaanalysis of undergraduate STEM education published to date. The results raise questions about the continued use of traditional lecturing as a control in research studies, and support active learning as the preferred, empirically validated teaching practice in regular classrooms.
01 Dec 2006-Biophysical Journal
TL;DR: A new method for fluorescence imaging has been developed that can obtain spatial distributions of large numbers of fluorescent molecules on length scales shorter than the classical diffraction limit, and suggests a means to address a significant number of biological questions that had previously been limited by microscope resolution.
Abstract: Biological structures span many orders of magnitude in size, but far-field visible light microscopy suffers from limited resolution. A new method for fluorescence imaging has been developed that can obtain spatial distributions of large numbers of fluorescent molecules on length scales shorter than the classical diffraction limit. Fluorescence photoactivation localization microscopy (FPALM) analyzes thousands of single fluorophores per acquisition, localizing small numbers of them at a time, at low excitation intensity. To control the number of visible fluorophores in the field of view and ensure that optically active molecules are separated by much more than the width of the point spread function, photoactivatable fluorescent mole- cules are used, in this case the photoactivatable green fluorescent protein (PA-GFP). For these photoactivatable molecules, the activation rate is controlled by the activation illumination intensity; nonfluorescent inactive molecules are activated by a high- frequency (405-nm) laser and are then fluorescent when excited at a lower frequency. The fluorescence is imaged by a CCD camera, and then the molecules are either reversibly inactivated or irreversibly photobleached to remove them from the field of view. The rate of photobleaching is controlled by the intensity of the laser used to excite the fluorescence, in this case an Ar1 ion laser. Because only a small number of molecules are visible at a given time, their positions can be determined precisely; with only ;100 detected photons per molecule, the localization precision can be as much as 10-fold better than the resolution, depending on background levels. Heterogeneities on length scales of the order of tens of nanometers are observed by FPALM of PA-GFP on glass. FPALM images are compared with images of the same molecules by widefield fluorescence. FPALM images of PA-GFP on a terraced sapphire crystal surface were compared with atomic force microscopy and show that the full width at half-maximum of features ;86 6 4 nm is significantly better than the expected diffraction-limited optical resolution. The number of fluorescent molecules and their brightness distribution have also been determined using FPALM. This new method suggests a means to address a significant number of biological questions that had previously been limited by microscope resolution.
TL;DR: Observations suggest that carbon nanotubes, with their rigid nonpolar structures, might be exploited as unique molecular channels for water and protons, with the channel occupancy and conductivity tunable by changes in the local channel polarity and solvent conditions.
Abstract: Confinement of matter on the nanometre scale can induce phase transitions not seen in bulk systems1. In the case of water, so-called drying transitions occur on this scale2,3,4,5 as a result of strong hydrogen-bonding between water molecules, which can cause the liquid to recede from nonpolar surfaces to form a vapour layer separating the bulk phase from the surface6. Here we report molecular dynamics simulations showing spontaneous and continuous filling of a nonpolar carbon nanotube with a one-dimensionally ordered chain of water molecules. Although the molecules forming the chain are in chemical and thermal equilibrium with the surrounding bath, we observe pulse-like transmission of water through the nanotube. These transmission bursts result from the tight hydrogen-bonding network inside the tube, which ensures that density fluctuations in the surrounding bath lead to concerted and rapid motion along the tube axis7,8,9. We also find that a minute reduction in the attraction between the tube wall and water dramatically affects pore hydration, leading to sharp, two-state transitions between empty and filled states on a nanosecond timescale. These observations suggest that carbon nanotubes, with their rigid nonpolar structures10,11, might be exploited as unique molecular channels for water and protons, with the channel occupancy and conductivity tunable by changes in the local channel polarity and solvent conditions.
Showing all 8637 results
|Clifford J. Rosen||111||655||47881|
|Juan S. Bonifacino||108||303||46554|
|John D. Aber||107||204||48500|
|Surendra P. Shah||99||710||32832|
|Charles T. Driscoll||97||554||37355|
|Patrick G. Hatcher||91||401||27519|
|Pedro J. J. Alvarez||89||378||34837|
|George R. Pettit||89||848||31759|
|James R. Wilson||89||1271||37470|
|Garry R. Buettner||80||304||29273|
|Paul Andrew Mayewski||80||420||29356|
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