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Institution

Oklahoma State University–Stillwater

EducationStillwater, 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
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Journal ArticleDOI
TL;DR: A literature review was done to present a summary of relevant literature on the general biology and ecology of the lesser grain borer to identify potential areas of further research on R. dominica.

178 citations

Journal ArticleDOI
TL;DR: In this article, the authors provided a global map and budget of the methane flux and degradation in diffusion-controlled marine sediments in relation to the depth of the Methane oxidation barrier.
Abstract: Anaerobic oxidation of methane provides a globally important, yet poorly constrained barrier for the vast amounts of methane produced in the subseafloor. Here we provide a global map and budget of the methane flux and degradation in diffusion-controlled marine sediments in relation to the depth of the methane oxidation barrier. Our new budget suggests that 45–61 Tg of methane are oxidized with sulfate annually, with approximately 80% of this oxidation occurring in continental shelf sediments (<200 m water depth). Using anaerobic oxidation as a nearly quantitative sink for methane in steady-state diffusive sediments, we calculate that ~3–4% of the global organic carbon flux to the seafloor is converted to methane. We further report a global imbalance of diffusive methane and sulfate fluxes into the sulfate–methane transition with no clear trend with respect to the corresponding depth of the methane oxidation barrier. The observed global mean net flux ratio between sulfate and methane of 1.4:1 indicates that, on average, the methane flux to the sulfate–methane transition accounts for only ~70% of the sulfate consumption in the sulfate–methane transition zone of marine sediments.

178 citations

Journal ArticleDOI
TL;DR: Percoll was a superior medium for efficient density gradient isolation of motile spermatozoa free of contamination by other seminal constituents.
Abstract: A procedure using centrifugation in density gradients composed of Percoll was developed for isolation of spermatozoa from mammalian semen. To evaluate the technique, rabbit, human, or bovine semen was layered over continuous Percoll gradients ranging in density from 1.02 to 1.13 gm/ml and centrifuged at 1,500g for 45 min. After centrifugation, the seminal plasma remained above the gradient, whereas the spermatozoa and seminal particles were distributed within the gradient according to their buoyant densities. Unlike most washing techniques, no sperm pellet was formed; instead, the spermatozoa were concentrated into a compact band above the most dense layer of Percoll. The spermatozoa recovered from the gradient were easily resuspended by gentle techniques. Thus, the mechanical stress to the spermatozoa was minimized. Osmotic stress to the spermatozoa was also negligible as the Percoll gradients were isotonic throughout. Spermatozoa obtained by this technique possessed motility equivalent to that of spermatozoa in the unfractionated semen. Sperm suspensions recovered from the gradients contained less than 5% of the nonspermatozoal particles present in the original samples of unfractionated semen. Soluble seminal components were also efficiently removed from the spermatozoa. Thirty billion bovine spermatozoa could be fractionated on a single gradient without loss of effectiveness. Recovery of spermatozoa from these preparative separations averaged 80%. These results demonstrated that Percoll was a superior medium for efficient density gradient isolation of motile spermatozoa free of contamination by other seminal constituents.

178 citations

Journal ArticleDOI
TL;DR: It is shown that CrackNet-V yields better overall performance particularly in detecting fine cracks compared with CrackNet, and further reveals the advantages of deep learning techniques for automated pixel-level pavement crack detection.
Abstract: A few recent developments have demonstrated that deep-learning-based solutions can outperform traditional algorithms for automated pavement crack detection. In this paper, an efficient deep network called CrackNet-V is proposed for automated pixel-level crack detection on 3D asphalt pavement images. Compared with the original CrackNet, CrackNet-V has a deeper architecture but fewer parameters, resulting in improved accuracy and computation efficiency. Inspired by CrackNet, CrackNet-V uses invariant spatial size through all layers such that supervised learning can be conducted at pixel level. Following the VGG network, CrackNet-V uses $3\times 3$ size of filters for the first six convolutional layers and stacks several $3\times 3$ convolutional layers together for deep abstraction, resulting in reduced number of parameters and efficient feature extraction. CrackNet-V has 64113 parameters and consists of ten layers, including one pre-process layer, eight convolutional layers, and one output layer. A new activation function leaky rectified tanh is proposed in this paper for higher accuracy in detecting shallow cracks. The training of CrackNet-V was completed after 3000 iterations, which took only one day on a GeForce GTX 1080Ti device. According to the experimental results on 500 testing images, CrackNet-V achieves a high performance with a Precision of 84.31%, Recall of 90.12%, and an F-1 score of 87.12%. It is shown that CrackNet-V yields better overall performance particularly in detecting fine cracks compared with CrackNet. The efficiency of CrackNet-V further reveals the advantages of deep learning techniques for automated pixel-level pavement crack detection.

178 citations

Journal ArticleDOI
TL;DR: In this article, geochronological and geochemical data from the Isthmus of Panama were used to reconstruct the closure of the Central American seaway at 15 Ma, suggesting that by the time of northern hemisphere glaciation, deep-water circulation had long been severed.
Abstract: Closure of the Central American seaway was a local tectonic event with potentially global biotic and environmental repercussions. We report geochronological (six U/Pb LA-ICP-MS zircon ages) and geochemical (19 XRF and ICP-MS analyses) data from the Isthmus of Panama that allow definition of a distinctive succession of plateau sequences to subduction-related protoarc to arc volcaniclastic rocks intruded by Late Cretaceous to middle Eocene intermediate plutonic rocks (67.6 ± 1.4 Ma to 41.1 ± 0.7 Ma). Paleomagnetic analyses (24 sites, 192 cores) in this same belt reveal large counterclockwise vertical-axis rotations (70.9° ± 6.7°), and moderate clockwise rotations (between 40° ± 4.1° and 56.2° ± 11.1°) on either side of an east-west trending fault at the apex of the Isthmus (Rio Gatun Fault), consistent with Isthmus curvature. An Oligocene-Miocene arc crosscuts the older, deformed and segmented arc sequences, and shows no significant vertical-axis rotation or deformation. There are three main stages of deformation: 1) left-lateral, strike-slip offset of the arc (∼100 km), and counterclockwise vertical-axis rotation of western arc segments between 38 and 28 Ma; 2) clockwise rotation of central arc segments between 28 and 25 Ma; and 3) orocline tightening after 25 Ma. When this reconstruction is placed in a global plate tectonic framework, and published exhumation data is added, the Central American seaway disappears at 15 Ma, suggesting that by the time of northern hemisphere glaciation, deep-water circulation had long been severed in Central America.

178 citations


Authors

Showing all 18403 results

NameH-indexPapersCitations
Gerald I. Shulman164579109520
James M. Tiedje150688102287
Robert J. Sternberg149106689193
Josh Moss139101989255
Brad Abbott137156698604
Itsuo Nakano135153997905
Luis M. Liz-Marzán13261661684
Flera Rizatdinova130124289525
Bernd Stelzer129120981931
Alexander Khanov129121987089
Dugan O'Neil128100080700
Michel Vetterli12890176064
Josu Cantero12684673616
Nicholas A. Kotov12357455210
Wei Chen122194689460
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202336
2022254
20211,902
20201,780
20191,633
20181,529