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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 mechanism for attractive mean forces between the plates is very different depending on the nature of the solute-solvent interaction which has implications for the mechanism of the hydrophobic effect for biomolecules.
Abstract: The hydration behavior of two planar nanoscopic hydrophobic solutes in liquid water at normal temperature and pressure is investigated by calculating the potential of mean force between them at constant pressure as a function of the solute-solvent interaction potential. The importance of the effect of weak attractive interactions between the solute atoms and the solvent on the hydration behavior is clearly demonstrated. We focus on the underlying mechanism behind the contrasting results obtained in various recent experimental and computational studies on water near hydrophobic solutes. The length scale where crossover from a solvent separated state to the contact pair state occurs is shown to depend on the solute sizes as well as on details of the solute-solvent interaction. We find the mechanism for attractive mean forces between the plates is very different depending on the nature of the solute-solvent interaction which has implications for the mechanism of the hydrophobic effect for biomolecules.

287 citations

Journal ArticleDOI
TL;DR: The authors showed empirically that regions with a more specialized production structure exhibit output fluctuations that are less correlated with those of other regions (less'symmetric' fluctuations) combined with the causal relation running from capital market integration to regional specialization found in an earlier study.

287 citations

Journal ArticleDOI
TL;DR: In this paper, the authors focus on robustness of model-predictive control with respect to satisfaction of process output constraints and propose a method of improving such robustness by formulating output constraints as chance constraints.
Abstract: This work focuses on robustness of model-predictive control with respect to satisfaction of process output constraints. A method of improving such robustness is presented. The method relies on formulating output constraints as chance constraints using the uncertainty description of the process model. The resulting on-line optimization problem is convex. The proposed approach is illustrated through a simulation case study on a high-purity distillation column. Suggestions for further improvements are made.

286 citations

Journal ArticleDOI
01 Mar 1993-Proteins
TL;DR: It is concluded that significant errors in energies can result from the neglect of ionization changes, and two novel methods for treating the energetics and forces associated with ionizable groups with a minimum of computer time have been developed.
Abstract: Computer models of proteins frequently treat the energies and forces associated with ionizable groups as if they were purely electrostatic. This paper examines the validity of the purely electrostatic approach, and concludes that significant errors in energies can result from the neglect of ionization changes. However, a complete treatment of ionizable groups presents substantial computational obstacles, because of the large number of ionization states which must be examined in systems having multiple interacting titratable groups. In order to address this problem, two novel methods for treating the energetics and forces associated with ionizable groups with a minimum of computer time have been developed. The most rapid method yields approximate energies by computing the free energy of a single highly occupied ionization state. The second method separates ionizable groups into clusters, and treats intracluster interactions exactly, but intercluster interactions approximately. This method yields both accurate energies and fractional charges. Good results are obtained in tests of both methods on proteins having has many as 123 ionizable groups. The more rapid method requires computer times of 0.01 to 0.34 sec, while the more accurate method requires 0.7 to 15 sec. These methods may be fast enough to permit the incorporation of ionization effects in iterative computations, such as energy minimizations and conformational searches. © 1993 Wiley-Liss, Inc.

286 citations

Journal ArticleDOI
TL;DR: A conflict bi-objective model for cost-emission based operation of industrial consumer in the presence of peak load management is proposed and fuzzy decision making approach is provided to select the trade-off solution from the Pareto solutions.

285 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