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: In this article, a set of 11 potential evaporation methods were compared in a global-scale water balance model (WBM) applied to 3265 0.5° (lat. × long.) grid cells representing the conterminous US.
447 citations
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TL;DR: The crystal structure of MDA5 bound to dsRNA is reported, which shows how, using the same domain architecture, MDA5 recognizes the internal duplex structure, whereas RIG-I recognizes the terminus of ds RNA.
446 citations
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Oak Ridge National Laboratory1, Griffith University2, University of Notre Dame3, Arizona State University4, Virginia Tech5, Michigan State University6, Spanish National Research Council7, Oregon State University8, Landcare Research9, Kansas State University10, University of New Hampshire11, University of Georgia12, Marine Biological Laboratory13
TL;DR: In this article, the authors studied whole-ecosystem metabolism in eight streams from several biomes in North America to identify controls on the rate of stream metabolism over a large geographic range.
Abstract: 'SUMMARY 1. We studied whole-ecosystem metabolism in eight streams from several biomes in North America to identify controls on the rate of stream metabolism over a large geographic range. The streams studied had climates ranging from tropical to cool-temperate and from humid to arid and were all relatively uninfluenced by human disturbances. 2. Rates of gross primary production (GPP), ecosystem respiration (R) and net ecosystem production (NEP) were determined using the open-system, two-station diurnal oxygen change method. 3. Three general patterns in metabolism were evident among streams: (1) relatively high GPP with positive NEP (i.e. net oxygen production) in early afternoon, (2) moderate primary production with a distinct peak in GPP during daylight but negative NEP at all times and (3) little or no evidence of GPP during daylight and a relatively constant and negative NEP over the entire day. ', 4. Gross primary production was most strongly correlated with photosynthetically active radiation (PAR). A multiple regression model that included log PAR and stream water soluble reactive phosphorus (SRP) concentration explained 90% of the variation in log GPP. 5. Ecosystem respiration was significantly correlated with SRP concentration and size of the transient storage zone and, together, these factors,explained 73% of the variation in R. The rate of R was poorly correlated with the rate of GPP. 6. Net ecosystem production was significantly correlated only with PAR, with 53% of the variation in log NEP explained by log PAR. Only Sycamore Creek, a desert stream in Arizona, had positive NEP (GPP: R > I), supporting the idea that streams are generally net sinks rather than net sources of organic matter.
445 citations
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TL;DR: It is shown how inexpensive, networked digital cameras ("webcams") can be used to document spatial and temporal variation in the spring and autumn phenology of forest canopies, and lays the foundation for regional- to continental-scale camera-based monitoring of phenology at network observatory sites, e.g., National Ecological Observatory Network (NEON) or AmeriFlux.
Abstract: There is a need to document how plant phenology is responding to global change factors, particularly warming trends. "Near-surface" remote sensing, using radiometric instruments or imaging sensors, has great potential to improve phenological monitoring because automated observations can be made at high temporal frequency. Here we build on previous work and show how inexpensive, networked digital cameras ("webcams") can be used to document spatial and temporal variation in the spring and autumn phenology of forest canopies. We use two years of imagery from a deciduous, northern hardwood site, and one year of imagery from a coniferous, boreal transition site. A quantitative signal is obtained by splitting images into separate red, green, and blue color channels and calculating the relative brightness of each channel for "regions of interest" within each image. We put the observed phenological signal in context by relating it to seasonal patterns of gross primary productivity, inferred from eddy covariance measurements of surface-atmosphere CO2 exchange. We show that spring increases, and autumn decreases, in canopy greenness can be detected in both deciduous and coniferous stands. In deciduous stands, an autumn red peak is also observed. The timing and rate of spring development and autumn senescence varies across the canopy, with greater variability in autumn than spring. Interannual variation in phenology can be detected both visually and quantitatively; delayed spring onset in 2007 compared to 2006 is related to a prolonged cold spell from day 85 to day 110. This work lays the foundation for regional- to continental-scale camera-based monitoring of phenology at network observatory sites, e.g., National Ecological Observatory Network (NEON) or AmeriFlux.
444 citations
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TL;DR: In this article, the authors consider right-censored survival data for populations with a surviving (cure) fraction and propose a model that is quite different from the standard mixture model for cure rates.
Abstract: We consider Bayesian methods for right-censored survival data for populations with a surviving (cure) fraction. We propose a model that is quite different from the standard mixture model for cure rates. We provide a natural motivation and interpretation of the model and derive several novel properties of it. First, we show that the model has a proportional hazards structure, with the covariates depending naturally on the cure rate. Second, we derive several properties of the hazard function for the proposed model and establish mathematical relationships with the mixture model for cure rates. Prior elicitation is discussed in detail, and classes of noninformative and informative prior distributions are proposed. Several theoretical properties of the proposed priors and resulting posteriors are derived, and comparisons are made to the standard mixture model. A real dataset from a melanoma clinical trial is discussed in detail.
444 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 |