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Institution

University of Luxembourg

EducationLuxembourg, Luxembourg
About: University of Luxembourg is a education organization based out in Luxembourg, Luxembourg. It is known for research contribution in the topics: Context (language use) & Computer science. The organization has 4744 authors who have published 22175 publications receiving 381824 citations.


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TL;DR: In this paper, the authors revisited the Foot and Frankel results on the sources of forward discount bias and found that the bias in the forward discount is due to the failure of rational expectations and the existence of time-varying risk premia.
Abstract: In this article we reconsider the Foot and Frankel results on the sources of forward discount bias. We question the economic validity of some estimation restrictions that they impose and, thus, are led to question some of their results. We employ a new exchange rate survey database that includes European Monetary System currencies and use univariate and pooling estimation techniques that impose fewer restrictions than those of Froot and Frankel to test our hypotheses. We find that the bias in the forward discount to BOTH (author emphasis) the failure of rational expectations and the existence of time-varying risk premia.

128 citations

Journal ArticleDOI
Michael C. Frank1, Katherine J. Alcock2, Natalia Arias-Trejo3, Gisa Aschersleben4, Dare A. Baldwin5, Stéphanie Barbu, Elika Bergelson6, Christina Bergmann7, Alexis K. Black8, Ryan Blything9, Maximilian P. Böhland10, Petra Bolitho11, Arielle Borovsky12, Shannon M. Brady13, Bettina Braun14, Anna Brown15, Krista Byers-Heinlein16, Linda E. Campbell17, Cara H. Cashon18, Mihye Choi19, Joan Christodoulou13, Laura K. Cirelli20, Stefania Conte21, Sara Cordes22, Christopher Martin Mikkelsen Cox23, Alejandrina Cristia, Rhodri Cusack24, Catherine Davies25, Maartje de Klerk26, Claire Delle Luche27, Laura E. de Ruiter28, Dhanya Dinakar29, Kate C. Dixon18, Virginie Durier, S. Durrant15, Christopher T. Fennell30, Brock Ferguson, Alissa L. Ferry28, Paula Fikkert31, Teresa Flanagan32, Caroline Floccia33, Megan Foley34, Tom Fritzsche35, Rebecca Louise Ann Frost7, Anja Gampe36, Judit Gervain, Nayeli Gonzalez-Gomez37, Anna Gupta38, Laura E. Hahn31, J. Kiley Hamlin39, Erin E. Hannon40, Naomi Havron, Jessica F. Hay41, Mikołaj Hernik42, Barbara Höhle35, Derek M. Houston43, Lauren H. Howard32, Mitsuhiko Ishikawa44, Shoji Itakura44, Iain Jackson28, Krisztina V. Jakobsen45, Marianna Jartó46, Scott P. Johnson13, Caroline Junge26, Didar Karadag47, Natalia Kartushina48, Danielle J. Kellier1, Tamar Keren-Portnoy23, Kelsey Klassen49, Melissa Kline50, Eon-Suk Ko51, Jonathan F. Kominsky52, Jessica E. Kosie5, Haley E. Kragness53, Andrea A. R. Krieger4, Florian Krieger54, Jill Lany55, Roberto J. Lazo56, Michelle Lee57, Chloé Leservoisier, Claartje Levelt38, Casey Lew-Williams58, Matthias Lippold59, Ulf Liszkowski46, Liquan Liu29, Steven G. Luke60, Rebecca A. Lundwall60, Viola Macchi Cassia21, Nivedita Mani59, Caterina Marino, Alia Martin11, Meghan Mastroberardino16, Victoria Mateu13, Julien Mayor48, Katharina Menn31, Christine Michel7, Yusuke Moriguchi44, Benjamin Morris61, Karli M. Nave40, Thierry Nazzi, Claire Noble15, Miriam A. Novack62, Nonah M. Olesen18, Adriel John Orena63, Mitsuhiko Ota64, Robin Panneton65, Sara Parvanezadeh Esfahani41, Markus Paulus66, Carolina Pletti66, Linda Polka63, Christine E. Potter58, Hugh Rabagliati64, Shruthilaya Ramachandran67, Jennifer L. Rennels40, Greg D. Reynolds41, Kelly C. Roth41, Charlotte Rothwell2, Doroteja Rubez43, Yana Ryjova40, Jenny R. Saffran68, Ayumi Sato69, Sophie Savelkouls22, Adena Schachner57, Graham Schafer70, Melanie S. Schreiner59, Amanda Seidl12, Mohinish Shukla19, Elizabeth A. Simpson56, Leher Singh67, Barbora Skarabela64, Gaye Soley47, Megha Sundara13, Anna L. Theakston28, Abbie Thompson55, Laurel J. Trainor53, Sandra E. Trehub20, Anna S. Trøan48, Angeline Sin-Mei Tsui30, Katherine Elizabeth Twomey28, Katie Von Holzen, Yuanyuan Wang43, Sandra R. Waxman62, Janet F. Werker39, Stephanie Wermelinger36, Alix Woolard17, Daniel Yurovsky61, Katharina Zahner14, Martin Zettersten68, Melanie Soderstrom49 
Stanford University1, Lancaster University2, National Autonomous University of Mexico3, Saarland University4, University of Oregon5, Duke University6, Max Planck Society7, Haskins Laboratories8, University of Bristol9, Dresden University of Technology10, Victoria University of Wellington11, Purdue University12, University of California, Los Angeles13, University of Konstanz14, University of Liverpool15, Concordia University16, University of Newcastle17, University of Louisville18, University of Massachusetts Boston19, University of Toronto20, University of Milan21, Boston College22, University of York23, Trinity College, Dublin24, University of Leeds25, Utrecht University26, University of Essex27, University of Manchester28, University of Sydney29, University of Ottawa30, Radboud University Nijmegen31, Franklin & Marshall College32, University of Plymouth33, Florida State University-Panama34, University of Potsdam35, University of Zurich36, Oxford Brookes University37, Leiden University38, University of British Columbia39, University of Nevada, Las Vegas40, University of Tennessee41, Central European University42, Ohio State University43, Kyoto University44, James Madison University45, University of Hamburg46, Boğaziçi University47, University of Oslo48, University of Manitoba49, Massachusetts Institute of Technology50, Chosun University51, Harvard University52, McMaster University53, University of Luxembourg54, University of Notre Dame55, University of Miami56, University of California, San Diego57, Princeton University58, University of Göttingen59, Brigham Young University60, University of Chicago61, Northwestern University62, McGill University63, University of Edinburgh64, Virginia Tech65, Ludwig Maximilian University of Munich66, National University of Singapore67, University of Wisconsin-Madison68, Shimane University69, University of Reading70
16 Mar 2020
TL;DR: In this paper, a large-scale, multisite study aimed at assessing the overall replicability of a single theoretically important phenomenon and examining methodological, cultural, and developmental moderators was conducted.
Abstract: Psychological scientists have become increasingly concerned with issues related to methodology and replicability, and infancy researchers in particular face specific challenges related to replicability: For example, high-powered studies are difficult to conduct, testing conditions vary across labs, and different labs have access to different infant populations. Addressing these concerns, we report on a large-scale, multisite study aimed at (a) assessing the overall replicability of a single theoretically important phenomenon and (b) examining methodological, cultural, and developmental moderators. We focus on infants’ preference for infant-directed speech (IDS) over adult-directed speech (ADS). Stimuli of mothers speaking to their infants and to an adult in North American English were created using seminaturalistic laboratory-based audio recordings. Infants’ relative preference for IDS and ADS was assessed across 67 laboratories in North America, Europe, Australia, and Asia using the three common methods for measuring infants’ discrimination (head-turn preference, central fixation, and eye tracking). The overall meta-analytic effect size (Cohen’s d) was 0.35, 95% confidence interval = [0.29, 0.42], which was reliably above zero but smaller than the meta-analytic mean computed from previous literature (0.67). The IDS preference was significantly stronger in older children, in those children for whom the stimuli matched their native language and dialect, and in data from labs using the head-turn preference procedure. Together, these findings replicate the IDS preference but suggest that its magnitude is modulated by development, native-language experience, and testing procedure.

128 citations

Journal ArticleDOI
TL;DR: Standard and robust generalized estimating equations (GEE) procedures were applied to quantify the importance of each effect on a piglet's probability of stillbirth, and standard and robust GEE approaches gave similar results despite some disequilibrium in the data set structure.
Abstract: Litter characteristics at birth were recorded in 4 genetic types of sows with differing maternal abilities. Eighty-two litters from F(1) Duroc x Large White sows, 651 litters from Large White sows, 63 litters from Meishan sows, and 173 litters from Laconie sows were considered. Statistical models included random effects of sow, litter, or both; fixed effects of sow genetic type, parity, birth assistance, and piglet sex, as well as gestation length, farrowing duration, piglet birth weight, and litter size as linear covariates. The quadratic components of the last 2 factors were also considered. For statistical analyses, GLM were first considered, assuming a binomial distribution of stillbirth. Hierarchical models were also fitted to the data to take into account correlations among piglets from the same litter. Model selection was performed based on deviance and deviance information criterion. Finally, standard and robust generalized estimating equations (GEE) procedures were applied to quantify the importance of each effect on a piglet's probability of stillbirth. The 5 most important factors involved were, in decreasing order (contribution of each effect to variance reduction): difference between piglet birth weight and the litter mean (2.36%), individual birth weight (2.25%), piglet sex (1.01%), farrowing duration (0.99%), and sow genetic type (0.94%). Probability of stillbirth was greater for lighter piglets, for male piglets, and for piglets from small or very large litters. Probability of stillbirth increased with sow parity number and with farrowing duration. Piglets born from Meishan sows had a lower risk of stillbirth (P < 0.0001) and were little affected by the sources of variation mentioned above compared with the 3 other sow genetic types. Standard and robust GEE approaches gave similar results despite some disequilibrium in the data set structure highlighted with the robust GEE approach.

128 citations

Journal ArticleDOI
TL;DR: It is demonstrated that loss of PTEN expression is an important factor in progression towards metastatic disease and could potentially serve as an early prognostic marker for prostate cancer metastasis.
Abstract: The EGF/IGF growth factors are potent mitogens that regulate cell proliferation and cell survival and are involved in prostate cancer development. Using laser microdissection technology and real-time PCR, together with immunohistochemistry, we have explored the growth factor and integrin dependent PI3-kinase/PTEN/Akt signalling pathway in prostate cell lines and tumour samples by analysing EGF-R, IGF1-R, ILK, beta3 integrin, PTEN and p-Akt protein expression. We provide evidence that loss of PTEN expression rather than upregulated EGF/IGF1 receptor expression was responsible for increased p-Akt in neoplastic prostate cells. We therefore compared PTEN expression in patient biopsies at first time diagnosis recruited prospectively (Study I, 112 patients) and patients with confirmed metastasis recruited retrospectively from the Luxembourg cancer registry (Study II, 42 patients). In Study I, loss of PTEN expression at first time diagnosis was found in 26 of 112 patients (23%). In Study II, 25 of the 42 patients (59%) with lymph node metastasis had complete loss of PTEN expression in both the neoplastic glands of the prostate and the invasive prostate cancer cells in the lymph node, and of these 13 (52%) exhibited already loss of PTEN expression at first diagnosis. These findings demonstrate that loss of PTEN expression is an important factor in progression towards metastatic disease and could potentially serve as an early prognostic marker for prostate cancer metastasis.

128 citations


Authors

Showing all 4893 results

NameH-indexPapersCitations
Jun Wang1661093141621
Leroy Hood158853128452
Andreas Heinz108107845002
Philippe Dubois101109848086
John W. Berry9735152470
Michael Müller9133326237
Bart Preneel8284425572
Bjorn Ottersten81105828359
Sander Kersten7924623985
Alexandre Tkatchenko7727126863
Rudi Balling7523819529
Lionel C. Briand7538024519
Min Wang7271619197
Stephen H. Friend7018453422
Ekhard K. H. Salje7058119938
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202360
2022250
20211,671
20201,776
20191,710
20181,663