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Institution

University of Kansas

EducationLawrence, Kansas, United States
About: University of Kansas is a education organization based out in Lawrence, Kansas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 38183 authors who have published 81381 publications receiving 2986312 citations. The organization is also known as: KU & Univ of Kansas.


Papers
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Journal ArticleDOI
TL;DR: The authors reconceptualized the source of motivation to suppress prejudice in terms of identifying with new reference groups and adapting oneself to fit new norms, and found that high suppressors are strong norm followers.
Abstract: The authors studied social norms and prejudice using M. Sherif and C. W. Sherif's (1953) group norm theory of attitudes. In 7 studies (N = 1,504), social norms were measured and manipulated to examine their effects on prejudice; both normatively proscribed and normatively prescribed forms of prejudice were included. The public expression of prejudice toward 105 social groups was very highly correlated with social approval of that expression. Participants closely adhere to social norms when expressing prejudice, evaluating scenarios of discrimination, and reacting to hostile jokes. The authors reconceptualized the source of motivation to suppress prejudice in terms of identifying with new reference groups and adapting oneself to fit new norms. Suppression scales seem to measure patterns of concern about group norms rather than personal commitments to reducing prejudice; high suppressors are strong norm followers. Compared with low suppressors, high suppressors follow normative rules more closely and are more strongly influenced by shifts in local social norms. There is much value in continuing the study of normative influence and self-adaptation to social norms, particularly in terms of the group norm theory of attitudes.

888 citations

Journal ArticleDOI
TL;DR: The results support the simple view of reading and the phonological deficit hypothesis and indicate that a classification system that is based on thesimple view has advantages over standard systems that focus only on word recognition and/or reading comprehension.
Abstract: Purpose To examine concurrently and retrospectively the language abilities of children with specific reading comprehension deficits (“poor comprehenders”) and compare them to typical readers and children with specific decoding deficits (“poor decoders”). Method In Study 1, the authors identified 57 poor comprehenders, 27 poor decoders, and 98 typical readers on the basis of 8th-grade reading achievement. These subgroups' performances on 8th-grade measures of language comprehension and phonological processing were investigated. In Study 2, the authors examined retrospectively subgroups' performances on measures of language comprehension and phonological processing in kindergarten, 2nd, and 4th grades. Word recognition and reading comprehension in 2nd and 4th grades were also considered. Results Study 1 showed that poor comprehenders had concurrent deficits in language comprehension but normal abilities in phonological processing. Poor decoders were characterized by the opposite pattern of language abilitie...

887 citations

Journal ArticleDOI
TL;DR: It is recommended that a biosensor should be clearly distinguished from a bioanalytical system, which requires additional processing steps, such as reagent addition, and a device which is both disposable after one measurement and unable to monitor the analyte concentration continuously or after rapid and reproducible regeneration should be designated a single use biosensor.
Abstract: Republication or reproduction of this report or its storage and/or dissemination by electronic means is permittedwithout the need for formal IUPAC permission on condition that an acknowledgement, with full reference to thesource along with use of the copyright symbol q, the name IUPAC and the year of publication are prominentlyvisible. Publication of a translation into another language is subject to the additional condition of prior approvalfrom the relevant IUPAC National Adhering Organization.

884 citations

Journal ArticleDOI
12 Sep 2007-PLOS ONE
TL;DR: The efficacy of Membrane Builder is illustrated by its applications to 12 transmembrane and 3 interfacial membrane proteins, whose fully equilibrated systems with three different types of lipid molecules and two types of system shapes are freely available on the CHARMM-GUI website.
Abstract: Molecular dynamics simulations of membrane proteins have provided deeper insights into their functions and interactions with surrounding environments at the atomic level. However, compared to solvation of globular proteins, building a realistic protein/membrane complex is still challenging and requires considerable experience with simulation software. Membrane Builder in the CHARMM-GUI website (http://www.charmm-gui.org) helps users to build such a complex system using a web browser with a graphical user interface. Through a generalized and automated building process including system size determination as well as generation of lipid bilayer, pore water, bulk water, and ions, a realistic membrane system with virtually any kinds and shapes of membrane proteins can be generated in 5 minutes to 2 hours depending on the system size. Default values that were elaborated and tested extensively are given in each step to provide reasonable options and starting points for both non-expert and expert users. The efficacy of Membrane Builder is illustrated by its applications to 12 transmembrane and 3 interfacial membrane proteins, whose fully equilibrated systems with three different types of lipid molecules (DMPC, DPPC, and POPC) and two types of system shapes (rectangular and hexagonal) are freely available on the CHARMM-GUI website. One of the most significant advantages of using the web environment is that, if a problem is found, users can go back and re-generate the whole system again before quitting the browser. Therefore, Membrane Builder provides the intuitive and easy way to build and simulate the biologically important membrane system.

883 citations

Journal ArticleDOI
TL;DR: The technique is designed to provide a thorough analysis of the relationship between an independent variable and the acquisition of a successive-approximation or chain sequence and provides answers to the following questions.
Abstract: Multiple-baseline and probe procedures are combined into a “multiple-probe” technique The technique is designed to provide a thorough analysis of the relationship between an independent variable and the acquisition of a successive-approximation or chain sequence It provides answers to the following questions: (1) What is the initial level of performance on each step in the training sequence? (2) What happens if sequential opportunities to perform each next step in the sequence are provided before training on that step? (3) What happens when training is applied? (4) What happens to the performance of remaining steps in the sequence as criterion is reached in the course of training each prior step? The technique features: (1) one initial probe of each step in the training sequence, (2) an additional probe of every step after criterion is reached on any training step, and (3) a series of “true” baseline sessions conducted just before the introduction of the independent variable to each training step Intermittent probes also provide an alternative to continuous baseline measurement, when such measurement during extended multiple baselines (1) may prove reactive, (2) is impractical, and/or (3) a strong a priori assumption of stability can be made

882 citations


Authors

Showing all 38401 results

NameH-indexPapersCitations
Gordon H. Guyatt2311620228631
Krzysztof Matyjaszewski1691431128585
Wei Li1581855124748
David Tilman158340149473
Tomas Hökfelt158103395979
Pete Smith1562464138819
Daniel J. Rader1551026107408
Melody A. Swartz1481304103753
Kevin Murphy146728120475
Carlo Rovelli1461502103550
Stephen Sanders1451385105943
Marco Zanetti1451439104610
Andrei Gritsan1431531135398
Gunther Roland1411471100681
Joseph T. Hupp14173182647
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202391
2022358
20214,211
20204,204
20193,766
20183,485