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Institution

University of Houston

EducationHouston, Texas, United States
About: University of Houston is a education organization based out in Houston, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 23074 authors who have published 53903 publications receiving 1641968 citations.


Papers
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Journal ArticleDOI
TL;DR: The authors examine a large sample of countries and find that a majority exhibit a significant structural break in their postwar growth rates, though not all of them exhibit significant structural change in the early 1970s.
Abstract: This paper proposes an explicit test for determining the significance and the timing of slowdowns in economic growth. We examine a large sample of countries and find that a majority—though not all—exhibit a significant structural break in their postwar growth rates. We find that (a) most industrialized countries experienced postwar growth slowdowns in the early 1970s, though (b) the United States, Canada, and the United Kingdom did not, and (c) developing countries (and in particular, Latin American countries) tended to experience much more severe slowdowns which, in contrast with the more developed countries, began nearly a decade later.

256 citations

Journal ArticleDOI
TL;DR: It is found that crowding exhibits spatial-tuning functions likemasking, but with generally broader bandwidths than those for masking, and that the magnitude of crowding increases monotonically with contrast ratio.

256 citations

Journal ArticleDOI
TL;DR: This paper investigates the optimal policy for user scheduling and resource allocation in HetNets powered by hybrid energy with the purpose of maximizing energy efficiency of the overall network and demonstrates the convergence property of the proposed algorithm.
Abstract: Densely deployment of various small-cell base stations in cellular networks to increase capacity will lead to heterogeneous networks (HetNets), and meanwhile, embedding the energy harvesting capabilities in base stations as an alternative energy supply is becoming a reality. How to make efficient utilization of radio resource and renewable energy is a brand-new challenge. This paper investigates the optimal policy for user scheduling and resource allocation in HetNets powered by hybrid energy with the purpose of maximizing energy efficiency of the overall network. Since wireless channel conditions and renewable energy arrival rates have stochastic properties and the environment’s dynamics are unknown, the model-free reinforcement learning approach is used to learn the optimal policy through interactions with the environment. To solve our problem with continuous-valued state and action variables, a policy-gradient-based actor-critic algorithm is proposed. The actor part uses the Gaussian distribution as the parameterized policy to generate continuous stochastic actions, and the policy parameters are updated with the gradient ascent method. The critic part uses compatible function approximation to estimate the performance of the policy and helps the actor learn the gradient of the policy. The advantage function is used to further reduce the variance of the policy gradient. Using the numerical simulations, we demonstrate the convergence property of the proposed algorithm and analyze network energy efficiency.

256 citations

Journal ArticleDOI
TL;DR: It is found that conditional deletion of Rictor in the postnatal murine forebrain greatly reduced mTORC2 activity and selectively impaired both long-term memory (LTM) and the late phase of hippocampal long- term potentiation (L-LTP).
Abstract: A major goal of biomedical research is the identification of molecular and cellular mechanisms that underlie memory storage. Here we report a previously unknown signaling pathway that is necessary for the conversion from short- to long-term memory. The mammalian target of rapamycin (mTOR) complex 2 (mTORC2), which contains the regulatory protein Rictor (rapamycin-insensitive companion of mTOR), was discovered only recently and little is known about its function. We found that conditional deletion of Rictor in the postnatal murine forebrain greatly reduced mTORC2 activity and selectively impaired both long-term memory (LTM) and the late phase of hippocampal long-term potentiation (L-LTP). We also found a comparable impairment of LTM in dTORC2-deficient flies, highlighting the evolutionary conservation of this pathway. Actin polymerization was reduced in the hippocampus of mTORC2-deficient mice and its restoration rescued both L-LTP and LTM. Moreover, a compound that promoted mTORC2 activity converted early LTP into late LTP and enhanced LTM. Thus, mTORC2 could be a therapeutic target for the treatment of cognitive dysfunction.

256 citations

Journal ArticleDOI
TL;DR: In this article, a beam-based paradigmatical design was proposed for flexoelectric energy harvesting under harmonic mechanical excitation. And the authors showed that the output power density and conversion efficiency increase significantly when the beam thickness reduces from micro-to nanoscale and flexolectricity-based energy harvesting can be a viable alternative to piezoelectrics.

256 citations


Authors

Showing all 23345 results

NameH-indexPapersCitations
Matthew Meyerson194553243726
Gad Getz189520247560
Eric Boerwinkle1831321170971
Pulickel M. Ajayan1761223136241
Zhenan Bao169865106571
Marc Weber1672716153502
Steven N. Blair165879132929
Martin Karplus163831138492
Dongyuan Zhao160872106451
Xiang Zhang1541733117576
Jan-Åke Gustafsson147105898804
James M. Tour14385991364
Guanrong Chen141165292218
Naomi J. Halas14043582040
Antonios G. Mikos13869470204
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023111
2022440
20213,031
20203,072
20192,806
20182,568