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Institution

DePaul University

EducationChicago, Illinois, United States
About: DePaul University is a education organization based out in Chicago, Illinois, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 5658 authors who have published 11562 publications receiving 295257 citations.


Papers
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Journal ArticleDOI
TL;DR: An information-processing view of the UN's cluster approach is used and it is shown that information quality is critical for effective resource utilization and if cluster leads filter information, it moves faster, enabling a prompt humanitarian response.
Abstract: The basis for this article is an information-processing view of the UN's cluster approach. We use agent-based modeling and simulations to show that clusters, if properly utilized, encourage better information flow and thus facilitate effective response to disasters. The article intends to turn the attention of the humanitarian community to the importance of sharing information and the role of cluster leads in facilitating humanitarian aid. Our results indicate that if cluster leads act as information hubs, information reaches its target faster, enabling a prompt humanitarian response. In addition, we show that information quality is critical for effective resource utilization-if cluster leads filter information, it moves faster. We also found evidence that the willingness to exchange information plays a larger role in transmitting information than that of an information hub, particularly during later stages of response operations.

162 citations

Journal ArticleDOI
01 May 2005-Planta
TL;DR: Based on the transport characteristics it appears as if the vacuolar uptake of SAG in tobacco cells occurs through an H+-antiport-type mechanism.
Abstract: The metabolism of salicylic acid (SA) in tobacco (Nicotiana tabacum L. cv. KY 14) cell suspension cultures was examined by adding [7−14C]SA to the cell cultures for 24 h and identifying the metabolites through high performance liquid chromatography analysis. The three major metabolites of SA were SA 2-O-β-D-glucose (SAG), methylsalicylate 2-O-β-D-glucose (MeSAG) and methylsalicylate. Studies on the intracellular localization of the metabolites revealed that all of the SAG associated with tobacco protoplasts was localized in the vacuole. However, the majority of the MeSAG was located outside the vacuole. The tobacco cells contained an SA inducible SA glucosyltransferase (SAGT) enzyme that formed SAG. The SAGT enzyme was not associated with the vacuole and appeared to be a cytoplasmic enzyme. The vacuolar transport of SAG was characterized by measuring the uptake of [14C]SAG into tonoplast vesicles isolated from tobacco cell cultures. SAG uptake was stimulated eightfold by the addition of MgATP. The ATP-dependent uptake of SAG was inhibited by bafilomycin A1 (a specific inhibitor of the vacuolar H+-ATPase) and dissipation of the transtonoplast H+-electrochemical gradient. Vanadate was not an inhibitor of SAG uptake. Several β-glucose conjugates were strong inhibitors of SAG uptake, whereas glutathione and glucuronide conjugates were only marginally inhibitory. The SAG uptake exhibited Michaelis–Menten type saturation kinetics with a Km and Vmax value of 11 μM and 205 pmol min−1 mg−1, respectively, for SAG. Based on the transport characteristics it appears as if the vacuolar uptake of SAG in tobacco cells occurs through an H+-antiport-type mechanism.

162 citations

Journal ArticleDOI
TL;DR: This work presents a matching algorithm that establishes many-to-many correspondences between the nodes of two noisy, vertex-labeled weighted graphs using a novel embedding technique based on a spherical encoding of graph structure.
Abstract: Object recognition can be formulated as matching image features to model features. When recognition is exemplar-based, feature correspondence is one-to-one. However, segmentation errors, articulation, scale difference, and within-class deformation can yield image and model features which don't match one-to-one but rather many-to-many. Adopting a graph-based representation of a set of features, we present a matching algorithm that establishes many-to-many correspondences between the nodes of two noisy, vertex-labeled weighted graphs. Our approach reduces the problem of many-to-many matching of weighted graphs to that of many-to-many matching of weighted point sets in a normed vector space. This is accomplished by embedding the initial weighted graphs into a normed vector space with low distortion using a novel embedding technique based on a spherical encoding of graph structure. Many-to-many vector correspondences established by the Earth Mover's Distance framework are mapped back into many-to-many correspondences between graph nodes. Empirical evaluation of the algorithm on an extensive set of recognition trials, including a comparison with two competing graph matching approaches, demonstrates both the robustness and efficacy of the overall approach.

162 citations

Journal ArticleDOI
TL;DR: In this article, a conceptual approach is taken to interpret and explain evolution in entrepreneurial thought, using the application of history to unify the extant and wide-ranging concepts underlying the field to detect a conceptual foundation.
Abstract: Purpose – To interpret and explain evolution in entrepreneurial thought, using the application of history to unify the extant and wide‐ranging concepts underlying the field to detect a conceptual foundation.Design/methodology/approach – A conceptual approach is taken, the paper undertaking a delineation of how past theory has brought about the field's current state and an identification of some conceptual areas for future advancement.Findings – The importance and impact of the entrepreneurship field is increasing in academic and practical settings. A historical view on the conceptual development of entrepreneurial thought provides a lens for scholars as well as practitioners to interpret and explain their own entrepreneurial activity or research and formulate new questions.Originality/value – The paper aids scholars and researchers to interpret and explain entrepreneurial activity.

162 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined the degree to which these elements of lean production are aided by investments in the supporting manufacturing infrastructure of the firm, and found that lean producers do invest in the development of the workforce and the support manufacturing infrastructure, rather than just paying lip service to the concept without following the underlying, core principles.
Abstract: Research on just‐in‐time (JIT) production and total quality management (TQM) has taken a variety of approaches. Focuses on the degree to which these elements of lean production are aided by investments in the supporting manufacturing infrastructure of the firm. The literature generally supports the hypothesis that manufacturers must support lean production with concurrent investments focusing on the training and development of the workforce in order to be successful. Uses data from a mail survey of 202 plants in the metalworking industries to examine this hypothesis. Examines four types of investment in the manufacturing infrastructure: quality leadership on the part of management, the use of small groups or teams for problem solving, training, and worker empowerment. Each of these types of infrastructural investment is shown to be highly correlated with the degree of managerial commitment to both JIT and TQM. Indicates that lean producers do invest in the development of the workforce and the supporting manufacturing infrastructure. Manufacturers in the metalworking industries appear to be making strong efforts to provide the necessary support to JIT and TQM programmes, rather than just paying lip service to the concept without following the underlying, core principles.

161 citations


Authors

Showing all 5724 results

NameH-indexPapersCitations
C. N. R. Rao133164686718
Mark T. Greenberg10752949878
Stanford T. Shulman8550234248
Paul Erdös8564034773
T. M. Crawford8527023805
Michael H. Dickinson7919623094
Hanan Samet7536925388
Stevan E. Hobfoll7427135870
Elias M. Stein6918944787
Julie A. Mennella6817813215
Raouf Boutaba6751923936
Paul C. Kuo6438913445
Gary L. Miller6330613010
Bamshad Mobasher6324318867
Gail McKoon6212514952
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202326
2022100
2021518
2020498
2019452
2018463