Institution
State University of New York System
Education•Albany, New York, United States•
About: State University of New York System is a education organization based out in Albany, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 54077 authors who have published 78070 publications receiving 2985160 citations.
Topics: Population, Poison control, Context (language use), Gene, Receptor
Papers published on a yearly basis
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TL;DR: In this paper, the authors exploit the deregulation of interstate bank branching laws to test whether banking competition affects innovation and find robust evidence that banking competition reduces state-level innovation by public corporations headquartered within deregulating states.
Abstract: We exploit the deregulation of interstate bank branching laws to test whether banking competition affects innovation. We find robust evidence that banking competition reduces state-level innovation by public corporations headquartered within deregulating states. Innovation increases among private firms that are dependent on external finance and that have limited access to credit from local banks. We argue that banking competition enables small, innovative firms to secure financing instead of being acquired by public corporations. Therefore, banking competition reduces the supply of innovative targets, which reduces the portion of state-level innovation attributable to public corporations. Overall, these results shed light on the real effects of banking competition and the determinants of innovation.
516 citations
TL;DR: The ADHD children showed behaviour during the extinction component that may well be described as a sustained-attention deficit: initially stopping when the signal was turned off and then resuming responding some time thereafter as if the signal had been turned on again.
515 citations
TL;DR: A new method named STM is described for determining distance of objects and rapid autofocusing of camera systems based on a new Spatial-Domain Convolution/Deconvolution Transform that requires only two images taken with different camera parameters such as lens position, focal length, and aperture diameter.
Abstract: A new method named STM is described for determining distance of objects and rapid autofocusing of camera systems. STM uses image defocus information and is based on a new Spatial-Domain Convolution/Deconvolution Transform. The method requires only two images taken with different camera parameters such as lens position, focal length, and aperture diameter. Both images can be arbitrarily blurred and neither of them needs to be a focused image. Therefore STM is very fast in comparison with Depth-from-Focus methods which search for the lens position or focal length of best focus. The method involves simple local operations and can be easily implemented in parallel to obtain the depth-map of a scene. STM has been implemented on an actual camera system named SPARCS. Experiments on the performance of STM and their results on real-world planar objects are presented. The results indicate that the accuracy of STM compares well with Depth-from-Focus methods and is useful in practical applications. The utility of the method is demonstrated for rapid autofocusing of electronic cameras.
514 citations
University of Amsterdam1, Harvard University2, Oslo University Hospital3, State University of New York System4, University of California, San Francisco5, Pfizer6, University of Sydney7, Wesley Hospital8, Queen Mary University of London9, University College London10, Touro University California11, University of Texas Health Science Center at San Antonio12, University of Dundee13, Cornell University14, University of Texas at Dallas15
TL;DR: Patients who achieve very low LDL-C levels have a lower risk for major cardiovascular events than do those achieving moderately low levels and the association between very low levels of atherogenic lipoproteins achieved with statin therapy and cardiovascular disease risk is well-documented.
514 citations
State University of New York System1, Centre de coopération internationale en recherche agronomique pour le développement2, ENEA3, University of Ottawa4, French Alternative Energies and Atomic Energy Commission5, Bioversity International6, Nestlé7, Bielefeld University8, Institut national de la recherche agronomique9, Chongqing University of Science and Technology10, University of Illinois at Urbana–Champaign11, University of Barcelona12, University of Maryland, College Park13, University of Trieste14, Empresa Brasileira de Pesquisa Agropecuária15, Analytica16, University of Queensland17, Coffee production in India18, University of Arizona19, Centre national de la recherche scientifique20, University of Évry Val d'Essonne21
TL;DR: The Coffea canephora (coffee) genome was sequenced and identified a conserved gene order, and comparative analyses of caffeine NMTs demonstrate that these genes expanded through sequential tandem duplications independently of genes from cacao and tea, suggesting that caffeine in eudicots is of polyphyletic origin.
Abstract: Coffee is a valuable beverage crop due to its characteristic flavor, aroma, and the stimulating effects of caffeine. We generated a high-quality draft genome of the species Coffea canephora, which displays a conserved chromosomal gene order among asterid angiosperms. Although it shows no sign of the whole-genome triplication identified in Solanaceae species such as tomato, the genome includes several species-specific gene family expansions, among them N-methyltransferases (NMTs) involved in caffeine production, defense-related genes, and alkaloid and flavonoid enzymes involved in secondary compound synthesis. Comparative analyses of caffeine NMTs demonstrate that these genes expanded through sequential tandem duplications independently of genes from cacao and tea, suggesting that caffeine in eudicots is of polyphyletic origin.
513 citations
Authors
Showing all 54162 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Meir J. Stampfer | 277 | 1414 | 283776 |
| Bert Vogelstein | 247 | 757 | 332094 |
| Zhong Lin Wang | 245 | 2529 | 259003 |
| Peter Libby | 211 | 932 | 182724 |
| Robert M. Califf | 196 | 1561 | 167961 |
| Stephen V. Faraone | 188 | 1427 | 140298 |
| David L. Kaplan | 177 | 1944 | 146082 |
| David Baker | 173 | 1226 | 109377 |
| Nora D. Volkow | 165 | 958 | 107463 |
| David R. Holmes | 161 | 1624 | 114187 |
| Richard J. Davidson | 156 | 602 | 91414 |
| Ronald G. Crystal | 155 | 990 | 86680 |
| Jovan Milosevic | 152 | 1433 | 106802 |
| James J. Collins | 151 | 669 | 89476 |
| Mark A. Rubin | 145 | 699 | 95640 |