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Institution

University at Buffalo

EducationBuffalo, New York, United States
About: University at Buffalo is a education organization based out in Buffalo, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 33773 authors who have published 63840 publications receiving 2278954 citations. The organization is also known as: UB & State University of New York at Buffalo.


Papers
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Journal ArticleDOI
TL;DR: The optical-limiting behavior and two-photon absorption properties of four novel organic compound solutions in tetrahydrofuran have been investigated and the molecular two- photon absorption coefficients are presented.
Abstract: The optical-limiting behavior and two-photon absorption properties of four novel organic compound solutions in tetrahydrofuran have been investigated. An ultrashort laser source with 0.5-ps pulse width and 602-nm wavelength was employed. The transmissivities of the various 1-cm-thick solution samples have been measured as a function of the beam intensity as well as of the solute concentration. The measured results can be fitted on the assumption that two-photon absorption is the only predominant mechanism causing the observed opticallimiting behavior. Based on the intensity-dependent transmissivity measurements, the molecular two-photon absorption coefficients for the four compounds are presented.

457 citations

Posted Content
TL;DR: In this article, the authors provided evidence of security analyst (SA) superiority relative to univariate time-series (TS) models in predicting firms' quarterly earnings numbers, and they demonstrated that SA forecast superiority in the sample is attributable to: 1. better use of information that exists on the date that TS model forecasts can be initiated, a contemporaneous advantage, and 2. Use of information acquired between the date of initiation of TS model forecast and the date when SA forecasts are published, a timing advantage.
Abstract: Evidence is provided of security analyst (SA) superiority relative to univariate time-series (TS) models in predicting firms' quarterly earnings numbers. It is demonstrated that SA forecast superiority in the sample is attributable to: 1. better use of information that exists on the date that TS model forecasts can be initiated, a contemporaneous advantage, and 2. use of information acquired between the date of initiation of TS model forecasts and the date when SA forecasts are published, a timing advantage.

457 citations

Journal ArticleDOI
TL;DR: Positive correlations are seen between the effects of six independent variables known to influence resistance to marrow grafts and the natural killer cell activity against mouse lymphomas in the NK system, indicating that the specificities of YAC‐1 and Hh‐1 incompatible targets were different.
Abstract: Two types of host reactivities not requiring immunization in the mouse and not mediated by T lymphocytes were compared: resistance of irradiated and nonirradiated F1 hybrids to accept parental grafts of normal or malignant hemopoietic cells (Hh system), and the natural killer cell activity against mouse lymphomas (NK system). The effects of six independent variables known to influence resistance to marrow grafts were investigated in the NK system using YAC-1 lymphoma cells as targets. The following properties were shared: (a) maturation during the fourth week of life; (b) low sensitivity to acute total body irradiation; (c) dependence on the integrity of bone marrow as demonstrated by reduced reactivity in 89Sr-treated mice; (d) suppression by a single injection of rabbit anti-mouse bone marrow serum; (e) suppression by a single injection of the anti-macrophage agents silica and i-carrageenan; and (f) suppression by multiple injections of parental spleen cells into F1 mice. These positive correlations are particularly significant because most of the variables have either opposing or no effect on conventional immunity. F1 mice rendered specifically unresponsive to parental marrow grafts, could retain NK cell activity, and genetically susceptible mice could be rendered hyporeactive in terms of NK cells, indicating that the specificities of YAC-1 and Hh-1 incompatible targets were different. It is extremely unlikely that this remarkable parallelism is fortuitous. These results indicate that either a very similar, or more likely a common mechanism is operative in the two cell-mediated natural reactivities: effector cells in the NK and Hh systems do not bear B or T lymphocyte markers but are nevertheless endowed with “specificity”. They are dependent for generation in vivo (presumably by maturation or by recruitment) on the interaction with nonlymphoid accessory cells not endowed with specificity, capable of also interacting in vitro with Thy-1-positive F1 hybrid prekiller cells specific for parental targets. Because of thymus independence in vivo and apparent restriction to target cells of the hemopoietic system, these reactivities should be effective in the regulation of hemopoiesis and surveillance over leukemogenesis.

456 citations

Journal ArticleDOI
TL;DR: In this article, the authors reported an efficient electrical injection of spin-polarized carriers from a non-lattice-matched magnetic contact into a semiconductor heterostructure.
Abstract: We report efficient electrical injection of spin-polarized carriers from a non-lattice-matched magnetic contact into a semiconductor heterostructure. The semimagnetic semiconductor ${\mathrm{Zn}}_{1\ensuremath{-}x}{\mathrm{Mn}}_{x}\mathrm{Se}$ is used as a spin-injecting contact on a GaAs-based light-emitting diode. Spin-polarized electrons are electrically injected across the II-VI/III-V interface, where they radiatively recombine in a GaAs quantum well and emit circularly polarized light. An analysis of the optical polarization which includes quantum confinement effects yields a lower bound of 50% for the spin injection efficiency.

454 citations

Journal ArticleDOI
Albert M. Sirunyan, Armen Tumasyan, Wolfgang Adam1, Federico Ambrogi1  +2238 moreInstitutions (159)
TL;DR: In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented.
Abstract: Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The b jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV).

454 citations


Authors

Showing all 34002 results

NameH-indexPapersCitations
Rakesh K. Jain2001467177727
Julie E. Buring186950132967
Anil K. Jain1831016192151
Donald G. Truhlar1651518157965
Roger A. Nicoll16539784121
Bruce L. Miller1631153115975
David R. Holmes1611624114187
Suvadeep Bose154960129071
Ashok Kumar1515654164086
Philip S. Yu1481914107374
Hugh A. Sampson14781676492
Aaron Dominguez1471968113224
Gregory R Snow1471704115677
J. S. Keller14498198249
C. Ronald Kahn14452579809
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202388
2022363
20212,772
20202,695
20192,527
20182,500