Institution
Oklahoma State University–Stillwater
Education•Stillwater, Oklahoma, United States•
About: Oklahoma State University–Stillwater is a education organization based out in Stillwater, Oklahoma, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 18267 authors who have published 36743 publications receiving 1107500 citations. The organization is also known as: Oklahoma State University & OKState.
Papers published on a yearly basis
Papers
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TL;DR: The performance of the missing transverse momentum reconstruction with the ATLAS detector is evaluated using data collected in proton–proton collisions at the LHC at a centre-of-mass energy of 13 TeV in 2015.
Abstract: The performance of the missing transverse momentum ( ETmiss ) reconstruction with the ATLAS detector is evaluated using data collected in proton-proton collisions at the LHC at a centre-of-mass energy of 13 TeV in 2015. To reconstruct ETmiss , fully calibrated electrons, muons, photons, hadronically decaying τ-leptons , and jets reconstructed from calorimeter energy deposits and charged-particle tracks are used. These are combined with the soft hadronic activity measured by reconstructed charged-particle tracks not associated with the hard objects. Possible double counting of contributions from reconstructed charged-particle tracks from the inner detector, energy deposits in the calorimeter, and reconstructed muons from the muon spectrometer is avoided by applying a signal ambiguity resolution procedure which rejects already used signals when combining the various ETmiss contributions. The individual terms as well as the overall reconstructed ETmiss are evaluated with various performance metrics for scale (linearity), resolution, and sensitivity to the data-taking conditions. The method developed to determine the systematic uncertainties of the ETmiss scale and resolution is discussed. Results are shown based on the full 2015 data sample corresponding to an integrated luminosity of 3.2fb-1 .
208 citations
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TL;DR: Free CLA in the products likely would be more readily available for absorption from the digestive tract than if it were incorporated into the cells of the starter culture.
208 citations
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Commonwealth Scientific and Industrial Research Organisation1, Institut national de la recherche agronomique2, China Agricultural University3, University of Bonn4, University of Göttingen5, United States Department of Agriculture6, International Maize and Wheat Improvement Center7, Oklahoma State University–Stillwater8, Prince of Songkla University9, Washington State University10, University of Florida11, James Hutton Institute12, University of Leeds13, CGIAR14, European Food Safety Authority15, Counterintelligence Field Activity16, Spanish National Research Council17, University of Córdoba (Spain)18, University of Guelph19, University of Maryland, College Park20, Texas A&M University21, Aarhus University22, Chinese Ministry of Agriculture23, Potsdam Institute for Climate Impact Research24, Indian Agricultural Research Institute25, Goddard Institute for Space Studies26, Rothamsted Research27, Michigan State University28, Queensland University of Technology29, University of Hohenheim30, Wageningen University and Research Centre31, Chinese Academy of Sciences32
TL;DR: A set of new temperature response functions are derived that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes, leading to higher skill of crop yield projections.
Abstract: Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.
208 citations
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TL;DR: In this paper, a chance constrained model is presented for the minimum cost design of water distribution networks, which attempts to account for the uncertainties in required demands, required pressure heads, and pipe roughness coefficients.
Abstract: A chance constrained model is presented for the minimum cost design of water distribution networks. This methodology attempts to account for the uncertainties in required demands, required pressure heads, and pipe roughness coefficients. The optimization problem is formulated as a nonlinear programming model which is solved using a generalized reduced gradient method. Details of the mathematical model formulation are presented along with example applications. Results illustrate that uncertainties in future demands, pressure head requirements, and pipe roughness can have significant effects on the optimal network design and cost.
207 citations
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01 May 2011TL;DR: This paper addresses natural human-robot interaction (HRI) in a smart assisted living (SAIL) system for the elderly and the disabled with a neural network for gesture spotting and a hierarchical hidden Markov model for context-based recognition.
Abstract: In this paper, we address natural human-robot interaction (HRI) in a smart assisted living (SAIL) system for the elderly and the disabled. Two common HRI problems are studied: hand gesture recognition and daily activity recognition. For hand gesture recognition, we implemented a neural network for gesture spotting and a hierarchical hidden Markov model for context-based recognition. For daily activity recognition, a multisensor fusion scheme is developed to process motion data collected from the foot and the waist of a human subject. Experiments using a prototype wearable sensor system show the effectiveness and accuracy of our algorithms.
207 citations
Authors
Showing all 18403 results
Name | H-index | Papers | Citations |
---|---|---|---|
Gerald I. Shulman | 164 | 579 | 109520 |
James M. Tiedje | 150 | 688 | 102287 |
Robert J. Sternberg | 149 | 1066 | 89193 |
Josh Moss | 139 | 1019 | 89255 |
Brad Abbott | 137 | 1566 | 98604 |
Itsuo Nakano | 135 | 1539 | 97905 |
Luis M. Liz-Marzán | 132 | 616 | 61684 |
Flera Rizatdinova | 130 | 1242 | 89525 |
Bernd Stelzer | 129 | 1209 | 81931 |
Alexander Khanov | 129 | 1219 | 87089 |
Dugan O'Neil | 128 | 1000 | 80700 |
Michel Vetterli | 128 | 901 | 76064 |
Josu Cantero | 126 | 846 | 73616 |
Nicholas A. Kotov | 123 | 574 | 55210 |
Wei Chen | 122 | 1946 | 89460 |