Institution
University of California, Santa Barbara
Education•Santa Barbara, California, United States•
About: University of California, Santa Barbara is a education organization based out in Santa Barbara, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 30281 authors who have published 80852 publications receiving 4626827 citations. The organization is also known as: UC Santa Barbara & UCSB.
Topics: Population, Galaxy, Laser, Quantum well, Quantum dot
Papers published on a yearly basis
Papers
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TL;DR: This report reports the first successful application of a dipole-surface type energy transfer from a molecular dipole to a nanometal surface that more than doubles the traditional Forster range (220 A) and follows a 1/R(4) distance dependence.
Abstract: Optical-based distance measurements are essential for tracking biomolecular conformational changes, drug discovery, and cell biology. Traditional Forster resonance energy transfer (FRET) is efficient for separation distances up to 100 A. We report the first successful application of a dipole-surface type energy transfer from a molecular dipole to a nanometal surface that more than doubles the traditional Forster range (220 A) and follows a 1/R4 distance dependence. We appended a 1.4 nm Au cluster to the 5‘ end of one DNA strand as the energy acceptor and a fluorescein (FAM) to the 5‘ end of the complementary strand as the energy donor. Analysis of the energy transfer on DNA lengths (15, 20, 30, 60bp), complemented by protein-induced DNA bending, provides the basis for fully mapping the extent of this dipole surface type mechanism over its entire usable range (50−250 A). Further, protein function is fully compatible with these nanometal−DNA constructs. Significantly extending the range of optical based met...
718 citations
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TL;DR: This work discusses Millennials’ communicated values and expectations and their potential effect on coworkers, as well as how workplace interaction may change Millennials.
Abstract: Stereotypes about Millennials, born between 1979 and 1994, depict them as self-centered, unmotivated, disrespectful, and disloyal, contributing to widespread concern about how communication with Millennials will affect organizations and how they will develop relationships with other organizational members. We review these purported characteristics, as well as Millennials’ more positive qualities—they work well in teams, are motivated to have an impact on their organizations, favor open and frequent communication with their supervisors, and are at ease with communication technologies. We discuss Millennials’ communicated values and expectations and their potential effect on coworkers, as well as how workplace interaction may change Millennials.
718 citations
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TL;DR: A scanning ion-conductance microscope (SICM) has been developed that can image the topography of nonconducting surfaces that are covered with electrolytes and sample and image the local ion currents above the surfaces.
Abstract: A scanning ion-conductance microscope (SICM) has been developed that can image the topography of nonconducting surfaces that are covered with electrolytes. The probe of the SICM is an electrolyte-filled micropipette. The flow of ions through the opening of the pipette is blocked at short distances between the probe and the surface, thus, limiting the ion conductance. A feedback mechanism can be used to maintain a given conductance and in turn determine the distance to the surface. The SICM can also sample and image the local ion currents above the surfaces. To illustrate its potential for imaging ion currents through channels in membranes, a topographic image of a membrane filter with 0.80-micrometer pores and an image of the ion currents flowing through such pores are presented.
717 citations
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Vardan Khachatryan, Albert M. Sirunyan, Armen Tumasyan, Wolfgang Adam1 +2197 more•Institutions (149)
TL;DR: The pre-print version of the Published Article can be accessed from the link below - Copyright @ 2010 Springer Verlag as discussed by the authors, which can be viewed as a preprint of the published article.
Abstract: This is the pre-print version of the Published Article, which can be accessed from the link below - Copyright @ 2010 Springer Verlag
717 citations
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TL;DR: This work proposes an algorithm to optimally estimate the overall distortion of decoder frame reconstruction due to quantization, error propagation, and error concealment and recursively computes the total decoder distortion at pixel level precision to accurately account for spatial and temporal error propagation.
Abstract: Resilience to packet loss is a critical requirement in predictive video coding for transmission over packet-switched networks, since the prediction loop propagates errors and causes substantial degradation in video quality. This work proposes an algorithm to optimally estimate the overall distortion of decoder frame reconstruction due to quantization, error propagation, and error concealment. The method recursively computes the total decoder distortion at pixel level precision to accurately account for spatial and temporal error propagation. The accuracy of the estimate is demonstrated via simulation results. The estimate is integrated into a rate-distortion (RD)-based framework for optimal switching between intra-coding and inter-coding modes per macroblock. The cost in computational complexity is modest. The framework is further extended to optimally exploit feedback/acknowledgment information from the receiver/network. Simulation results both with and without a feedback channel demonstrate that precise distortion estimation enables the coder to achieve substantial and consistent gains in PSNR over known state-of-the-art RD- and non-RD-based mode switching methods.
717 citations
Authors
Showing all 30652 results
Name | H-index | Papers | Citations |
---|---|---|---|
George M. Whitesides | 240 | 1739 | 269833 |
Yi Chen | 217 | 4342 | 293080 |
Simon D. M. White | 189 | 795 | 231645 |
George Efstathiou | 187 | 637 | 156228 |
Peidong Yang | 183 | 562 | 144351 |
David R. Williams | 178 | 2034 | 138789 |
Alan J. Heeger | 171 | 913 | 147492 |
Richard H. Friend | 169 | 1182 | 140032 |
Jiawei Han | 168 | 1233 | 143427 |
Gang Chen | 167 | 3372 | 149819 |
Alexander S. Szalay | 166 | 936 | 145745 |
Omar M. Yaghi | 165 | 459 | 163918 |
Carlos S. Frenk | 165 | 799 | 140345 |
Yang Yang | 164 | 2704 | 144071 |
Carlos Bustamante | 161 | 770 | 106053 |