scispace - formally typeset
Search or ask a question
Institution

Oregon State University

EducationCorvallis, Oregon, United States
About: Oregon State University is a education organization based out in Corvallis, Oregon, United States. It is known for research contribution in the topics: Population & Climate change. The organization has 28192 authors who have published 64044 publications receiving 2634108 citations. The organization is also known as: Oregon Agricultural College & OSU.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, the characteristics of the zonal-mean circulation and how it responds to seasonal variations and dust loading are described, and the radiative effects of suspended dust particles, even in small amounts, have a major influence on the general circulation.
Abstract: The characteristics of the zonal-mean circulation and how it responds to seasonal variations and dust loading are described. This circulation is the main momentum-containing component of the general circulation, and it plays a dominant role in the budgets of heat and momentum. It is shown that in many ways the zonal-mean circulation on Mars, at least as simulated by the model, is similar to that on earth, having Hadley and Ferrel cells and high-altitude jet streams. However, the Martian systems tend to be deeper, more intense, and much more variable with season. Furthermore, the radiative effects of suspended dust particles, even in small amounts, have a major influence on the general circulation.

373 citations

Journal ArticleDOI
TL;DR: The authors assess the relationship between four antecedents (social mission/motivation, opportunity identification, access to resources/funding, and multiple stakeholders) and three outcomes (social value creation, sustainable solutions, and satisfying multiple stakeholders).
Abstract: Scholars have compared and contrasted commercial and social entrepreneurship along a variety of dimensions, suggesting that entrepreneurial antecedents and outcomes differ within a social context. However, little is known about whether entrepreneurial processes differ within social contexts. In this paper, we ask to what extent the antecedents and outcomes that make social entrepreneurship unique influence entrepreneurial processes. Using an inputs–throughputs–outputs framework, we assess the relationship between four antecedents (social mission/motivation, opportunity identification, access to resources/funding, and multiple stakeholders) and three outcomes (social value creation, sustainable solutions, and satisfying multiple stakeholders) to the dimensions of entrepreneurial orientation (innovativeness, proactiveness, risk-taking, competitive aggressiveness, and autonomy) (Lumpkin and Dess, Acad Manag Rev 21(1):135–172, 1996). Our analysis suggests that many entrepreneurial processes remain essentially the same or are affected only slightly. However, autonomy, competitive aggressiveness, and risk-taking are influenced to some extent by the presence of multiple stakeholders and access to resources/funding. Entrepreneurial processes may also differ when applied to efforts to satisfy multiple stakeholders and achieve sustainable solutions. We subsequently discuss the implications of our analysis for future social entrepreneurship research and practice.

373 citations

Proceedings ArticleDOI
27 Jun 2016
TL;DR: This paper presents a novel deep architecture, called neural regression forest (NRF), for depth estimation from a single image, which combines random forests and convolutional neural networks (CNNs).
Abstract: This paper presents a novel deep architecture, called neural regression forest (NRF), for depth estimation from a single image. NRF combines random forests and convolutional neural networks (CNNs). Scanning windows extracted from the image represent samples which are passed down the trees of NRF for predicting their depth. At every tree node, the sample is filtered with a CNN associated with that node. Results of the convolutional filtering are passed to left and right children nodes, i.e., corresponding CNNs, with a Bernoulli probability, until the leaves, where depth estimations are made. CNNs at every node are designed to have fewer parameters than seen in recent work, but their stacked processing along a path in the tree effectively amounts to a deeper CNN. NRF allows for parallelizable training of all "shallow" CNNs, and efficient enforcing of smoothness in depth estimation results. Our evaluation on the benchmark Make3D and NYUv2 datasets demonstrates that NRF outperforms the state of the art, and gracefully handles gradually decreasing training datasets.

372 citations

Journal ArticleDOI
TL;DR: In this article, micro-crystalline barites recovered by deep-sea drilling from Site 684 on the Peru margin and Site 799 in the Japan Sea are highly enriched in the heavy sulfur isotope relative to seawater (δ34S up to + 84%).

372 citations

Journal ArticleDOI
TL;DR: Ten different fluorochemical classes were identified in the seven military-certified AFFF formulations and include anionic, cationic, and zwitterionic surfactants with perfluoroalkyl chain lengths ranging from 4 to 12, and the environmental implications are discussed, and research needs are identified.
Abstract: Aqueous film-forming foams (AFFFs) are a vital tool to fight large hydrocarbon fires and can be used by public, commercial, and military firefighting organizations. In order to possess these superior firefighting capabilities, AFFFs contain fluorochemical surfactants, of which many of the chemical identities are listed as proprietary. Large-scale controlled (e.g., training activities) and uncontrolled releases of AFFF have resulted in contamination of groundwater. Information on the composition of AFFF formulations is needed to fully define the extent of groundwater contamination, and the first step is to fully define the fluorochemical composition of AFFFs used by the US military. Fast atom bombardment mass spectrometry (FAB-MS) and high resolution quadrupole-time-of-flight mass spectrometry (QTOF-MS) were combined to elucidate chemical formulas for the fluorochemicals in AFFF mixtures, and, along with patent-based information, structures were assigned. Sample collection and analysis was focused on AFFFs...

372 citations


Authors

Showing all 28447 results

NameH-indexPapersCitations
Robert Stone1601756167901
Menachem Elimelech15754795285
Thomas J. Smith1401775113919
Harold A. Mooney135450100404
Jerry M. Melillo13438368894
John F. Thompson132142095894
Thomas N. Williams132114595109
Peter M. Vitousek12735296184
Steven W. Running12635576265
Vincenzo Di Marzo12665960240
J. D. Hansen12297576198
Peter Molnar11844653480
Michael R. Hoffmann10950063474
David Pollard10843839550
David J. Hill107136457746
Network Information
Related Institutions (5)
University of California, Davis
180K papers, 8M citations

94% related

University of Illinois at Urbana–Champaign
225.1K papers, 10.1M citations

94% related

Pennsylvania State University
196.8K papers, 8.3M citations

93% related

University of Florida
200K papers, 7.1M citations

93% related

University of Maryland, College Park
155.9K papers, 7.2M citations

93% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023105
2022375
20213,156
20203,109
20193,017
20182,987