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Institution

Pennsylvania State University

EducationState College, Pennsylvania, United States
About: Pennsylvania State University is a education organization based out in State College, Pennsylvania, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 79763 authors who have published 196876 publications receiving 8318601 citations. The organization is also known as: Penn State & PSU.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors argue that goal orientation is a two-dimensional construct that has both dispostional and situational components and provide a foundation for future organizational research in this area.

1,164 citations

Journal ArticleDOI
TL;DR: In this article, a survey of 1,000 property owners in a lake-rich region (the Northern Highlands Lake District of Northern Wisconsin) was conducted and the best fit model integrating environmental variables with sense of place was a meaning mediated model that considered certain landscape attributes (i.e., level of shoreline development) as predictive of certain meanings related to attachment and satisfaction.
Abstract: Although sense of place definitions nominally include the physical environment, much research has emphasized the social construction of sense of place and neglect the potentially important contributions of the physical environment to place meanings and attachment. This article presents research that tests several models that integrate (1) characteristics of the environment, (2) human uses of the environment, (3) constructed meanings, and (4) place attachment and satisfaction. The research utilized a mail survey of 1,000 property owners in a lake-rich region (the Northern Highlands Lake District of Northern Wisconsin). Structural equation modeling revealed that the best fit model integrating environmental variables with sense of place was a meaning-mediated model that considered certain landscape attributes (i.e., level of shoreline development) as predictive of certain meanings related to attachment and satisfaction. This research demonstrates that landscape attributes matter a great deal to constructed m...

1,164 citations

Journal ArticleDOI
TL;DR: This paper implemented and tested the ALIP (Automatic Linguistic Indexing of Pictures) system on a photographic image database of 600 different concepts, each with about 40 training images and demonstrated the good accuracy of the system and its high potential in linguistic indexing of photographic images.
Abstract: Automatic linguistic indexing of pictures is an important but highly challenging problem for researchers in computer vision and content-based image retrieval. In this paper, we introduce a statistical modeling approach to this problem. Categorized images are used to train a dictionary of hundreds of statistical models each representing a concept. Images of any given concept are regarded as instances of a stochastic process that characterizes the concept. To measure the extent of association between an image and the textual description of a concept, the likelihood of the occurrence of the image based on the characterizing stochastic process is computed. A high likelihood indicates a strong association. In our experimental implementation, we focus on a particular group of stochastic processes, that is, the two-dimensional multiresolution hidden Markov models (2D MHMMs). We implemented and tested our ALIP (Automatic Linguistic Indexing of Pictures) system on a photographic image database of 600 different concepts, each with about 40 training images. The system is evaluated quantitatively using more than 4,600 images outside the training database and compared with a random annotation scheme. Experiments have demonstrated the good accuracy of the system and its high potential in linguistic indexing of photographic images.

1,163 citations

Journal ArticleDOI
TL;DR: Loop quantum cosmology (LQC) as mentioned in this paper is the result of applying principles of loop quantum gravity to cosmological settings, where quantum geometry creates a brand new repulsive force which is totally negligible at low spacetime curvature but rises very rapidly in the Planck regime, overwhelming the classical gravitational attraction.
Abstract: Loop quantum cosmology (LQC) is the result of applying principles of loop quantum gravity (LQG) to cosmological settings. The distinguishing feature of LQC is the prominent role played by the quantum geometry effects of LQG. In particular, quantum geometry creates a brand new repulsive force which is totally negligible at low spacetime curvature but rises very rapidly in the Planck regime, overwhelming the classical gravitational attraction. In cosmological models, while Einstein's equations hold to an excellent degree of approximation at low curvature, they undergo major modifications in the Planck regime: for matter satisfying the usual energy conditions, any time a curvature invariant grows to the Planck scale, quantum geometry effects dilute it, thereby resolving singularities of general relativity. Quantum geometry corrections become more sophisticated as the models become richer. In particular, in anisotropic models, there are significant changes in the dynamics of shear potentials which tame their singular behavior in striking contrast to older results on anisotropies in bouncing models. Once singularities are resolved, the conceptual paradigm of cosmology changes and one has to revisit many of the standard issues—e.g. the 'horizon problem'—from a new perspective. Such conceptual issues as well as potential observational consequences of the new Planck scale physics are being explored, especially within the inflationary paradigm. These considerations have given rise to a burst of activity in LQC in recent years, with contributions from quantum gravity experts, mathematical physicists and cosmologists. The goal of this review is to provide an overview of the current state of the art in LQC for three sets of audiences: young researchers interested in entering this area; the quantum gravity community in general and cosmologists who wish to apply LQC to probe modifications in the standard paradigm of the early universe. In this review, effort has been made to streamline the material so that each of these communities can read only the sections they are most interested in, without loss of continuity.

1,162 citations

Journal ArticleDOI
TL;DR: It is shown that the hypercitrullination of histones by PAD4 mediates chromatin decondensation in granulocytes/neutrophils, and citrullinations of biochemically defined avian nucleosome arrays inhibits their compaction by the linker histone H5 to form higher order chromatin structures.
Abstract: Peripheral blood neutrophils form highly decondensed chromatin structures, termed neutrophil extracellular traps (NETs), that have been implicated in innate immune response to bacterial infection. Neutrophils express high levels of peptidylarginine deiminase 4 (PAD4), which catalyzes histone citrullination. However, whether PAD4 or histone citrullination plays a role in chromatin structure in neutrophils is unclear. In this study, we show that the hypercitrullination of histones by PAD4 mediates chromatin decondensation. Histone hypercitrullination is detected on highly decondensed chromatin in HL-60 granulocytes and blood neutrophils. The inhibition of PAD4 decreases histone hypercitrullination and the formation of NET-like structures, whereas PAD4 treatment of HL-60 cells facilitates these processes. The loss of heterochromatin and multilobular nuclear structures is detected in HL-60 granulocytes after PAD4 activation. Importantly, citrullination of biochemically defined avian nucleosome arrays inhibits their compaction by the linker histone H5 to form higher order chromatin structures. Together, these results suggest that histone hypercitrullination has important functions in chromatin decondensation in granulocytes/neutrophils.

1,162 citations


Authors

Showing all 80524 results

NameH-indexPapersCitations
Robert Langer2812324326306
Zhong Lin Wang2452529259003
Donald P. Schneider2421622263641
David J. Hunter2131836207050
Robert M. Califf1961561167961
Martin White1962038232387
Eric J. Topol1931373151025
Charles A. Dinarello1901058139668
Jing Wang1844046202769
Dennis S. Charney179802122408
David Haussler172488224960
Chad A. Mirkin1641078134254
Ian A. Wilson15897198221
David Cella1561258106402
Jay Hauser1552145132683
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023278
20221,326
20219,400
20209,372
20198,765
20188,150