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Institution

Université catholique de Louvain

EducationLouvain-la-Neuve, Belgium
About: Université catholique de Louvain is a education organization based out in Louvain-la-Neuve, Belgium. It is known for research contribution in the topics: Population & Catalysis. The organization has 25319 authors who have published 57360 publications receiving 2172080 citations. The organization is also known as: University of Louvain & UCLouvain.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors present a derivation of a (local) measure of risk aversion for delayed risks which, like the Pratt measure in the timeless context, represents twice the risk premium per unit of variance for infinitesimal risks.

557 citations

Journal ArticleDOI
TL;DR: In this article, the authors survey the contributions made so far on the social networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues.
Abstract: In this paper, we review some advances made recently in the study of mobile phone datasets. This area of research has emerged a decade ago, with the increasing availability of large-scale anonymized datasets, and has grown into a stand-alone topic. We survey the contributions made so far on the social networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues.

556 citations

Journal ArticleDOI
TL;DR: This review summarizes the exciting developments in the understanding of tryptophan catabolism as a key factor in the immunobiology of cancer.
Abstract: Tryptophan catabolism in cancer is increasingly being recognized as an important microenvironmental factor that suppresses antitumor immune responses. It has been proposed that the essential amino acid tryptophan is catabolized in the tumor tissue by the rate-limiting enzyme indoleamine-2,3-dioxygenase (IDO) expressed in tumor cells or antigen-presenting cells. This metabolic pathway creates an immunosuppressive milieu in tumors and in tumor-draining lymph nodes by inducing T-cell anergy and apoptosis through depletion of tryptophan and accumulation of immunosuppressive tryptophan catabolites. Competitive inhibitors of IDO are currently being tested in clinical trials in patients with solid cancer, with the aim of enhancing the efficacy of conventional chemotherapy. There are, however, certain tumor types that are capable of catabolizing tryptophan but are largely IDO-negative. Recent evidence from studies in malignant gliomas and other types of cancers points to alternative enzymatic pathways of tryptophan catabolism involving tryptophan-2,3-dioxygenase (TDO). TDO, which is considered responsible for regulating systemic tryptophan levels in the liver, is constitutively expressed in some cancers and is equally capable of suppressing antitumor immune responses. Depletion of tryptophan induces signaling events in T cells, leading to anergy and apoptosis; however, active immunomodulation by accumulating tryptophan catabolites, most notably kynurenine, appears to play an equally important role. These immunomodulatory effects of kynurenine are mediated by the aryl hydrocarbon receptor. This intracellular transcription factor has classically been viewed as a receptor for environmental toxins, such as dioxin, and its important role in influencing immune responses, especially in epithelial barriers, is only beginning to emerge. This review summarizes the exciting developments in our understanding of tryptophan catabolism as a key factor in the immunobiology of cancer.

556 citations

Journal ArticleDOI
TL;DR: In this article, the authors employ text mining to extract changes in affective content and linguistic style properties of customer book reviews on Amazon.com, and find that positive changes of affective cues and increasing congruence with the product interest group's typical linguistic style directly and conjointly increase conversion rates.
Abstract: Customers increasingly rely on other consumers' reviews to make purchase decisions online. New insights into the customer review phenomenon can be derived from studying the semantic content and style properties of verbatim customer reviews to examine their influence on online retail sites' conversion rates. The authors employ text mining to extract changes in affective content and linguistic style properties of customer book reviews on Amazon.com. A dynamic panel data model reveals that the influence of positive affective content on conversion rates is asymmetrical, such that greater increases in positive affective content in customer reviews have a smaller effect on subsequent increases in conversion rate. No such tapering-off effect occurs for changes in negative affective content in reviews. Furthermore, positive changes in affective cues and increasing congruence with the product interest group's typical linguistic style directly and conjointly increase conversion rates. These findings suggest that managers should identify and promote the most influential reviews in a given product category, provide instructions to stimulate reviewers to write powerful reviews, and adapt the style of their own editorial reviews to the relevant product category.

555 citations

Journal ArticleDOI
TL;DR: In this paper, stable algorithms for the computation of the Kronecker structure of an arbitrary pencil were developed, which can be viewed as a generalization of the wellknown eigenvalue problem of pencils of the type LambdaI-A.

555 citations


Authors

Showing all 25540 results

NameH-indexPapersCitations
Robert Langer2812324326306
Pulickel M. Ajayan1761223136241
Klaus Müllen1642125140748
Giacomo Bruno1581687124368
Willem M. de Vos14867088146
David Goldstein1411301101955
Krzysztof Piotrzkowski141126999607
Andrea Giammanco135136298093
Christophe Delaere135132096742
Vincent Lemaitre134131099190
Michael Tytgat134144994133
Jian Li133286387131
Jost B. Jonas1321158166510
George Stephans132133786865
Peter Hall132164085019
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023147
2022424
20212,952
20202,969
20192,752
20182,676