scholarly journals A Quasi-Static Model for Craquelure Patterns

Author(s):  
Matteo Negri
Keyword(s):  
2020 ◽  
pp. 375-381
Author(s):  
A.V. Tsepkova

The paper analyses metaphorical patterns of coining contemporary Russian anthroponymic nicknames representing the nominee's character and behaviour. It is concluded that the motives under analysis are more frequent within the static model Person is the bearer of qualities (56,5 %), the most frequent source domain being the domain of living beings (man: 46,7 %; animal: 31,5 %). 68 % of nicknames have negative connotations, prevailing in cases drawn from the source domains Man (37 %) and Lifeless thing (9,8 %).


2020 ◽  
pp. 052
Author(s):  
Jean-Christophe Calvet ◽  
Jean-Louis Champeaux

Cet article présente les différentes étapes des développements réalisés au CNRM des années 1990 à nos jours pour spatialiser à diverses échelles les simulations du modèle Isba des surfaces terrestres. Une attention particulière est portée sur l'intégration, dans le modèle, de données satellitaires permettant de caractériser la végétation. Deux façons complémentaires d'introduire de l'information géographique dans Isba sont présentées : cartographie de paramètres statiques et intégration au fil de l'eau dans le modèle de variables observables depuis l'espace. This paper presents successive steps in developments made at CNRM from the 1990s to the present-day in order to spatialize the simulations of the Isba land surface model at various scales. The focus is on the integration in the model of satellite data informative about vegetation. Two complementary ways to integrate geographic information in Isba are presented: mapping of static model parameters and sequential assimilation of variables observable from space.


Author(s):  
Bruno Maçães

Popular consensus says that the US rose over two centuries to Cold War victory and world domination, and is now in slow decline. But is this right? History's great civilizations have always lasted much longer, and for all its colossal power, American culture was overshadowed by Europe until recently. What if this isn't the end? This book offers a compelling vision of America's future, both fascinating and unnerving. From the early American Republic, it takes us to the turbulent present, when, it argues, America is finally forging its own path. We can see the birth pangs of this new civilization in today's debates on guns, religion, foreign policy, and the significance of Trump. Should the coronavirus pandemic be regarded as an opportunity to build a new kind of society? What will its values be, and what will this new America look like? The book traces the long arc of US history to argue that in contrast to those who see the US on the cusp of decline, it may well be simply shifting to a new model, one equally powerful but no longer liberal. Consequently, it is no longer enough to analyze America's current trajectory through the simple prism of decline vs. progress, which assumes a static model—America as liberal leviathan. Rather, the book argues that America may be casting off the liberalism that has defined the country since its founding for a new model, one more appropriate to succeeding in a transformed world.


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Filippo Belloc

AbstractWe study hours worked by drivers in the peer-to-peer transportation sector with cross-side network effects. Medallion lease (regulated market), commission-based (Uber-like pay) and profit-sharing (“pure” taxi coop) compensation schemes are compared. Our static model shows that network externalities matter, depending on the number of active drivers. When the number of drivers is limited, in the presence of positive network effects, a regulated system always induces more hours worked, while the commission fee influences the comparative incentives towards working time of Uber-like pay versus profit-sharing. When the number of drivers is infinite (or close to it), the influence of network externalities on optimal working time vanishes. Our model helps identifying which is the pay scheme that best remunerates longer working times and offers insights to regulators seeking to improve the intensive margin of coverage by taxi services.


2021 ◽  
Author(s):  
T. V. Matyushev ◽  
M. V. Dvornikov ◽  
S. P. Ryzhenkov ◽  
M. A. Petrov

2021 ◽  
Vol 14 (3) ◽  
pp. 125
Author(s):  
Erol Muzir ◽  
Cevdet Kizil ◽  
Burak Ceylan

This paper aims to develop some static and conditional (dynamic) models to predict portfolio returns in the Borsa Istanbul (BIST) that are calibrated to combine the capital asset-pricing model (CAPM) and corporate governance quality. In our conditional model proposals, both the traditional CAPM (beta) coefficient and model constant are allowed to vary on a binary basis with any degradation or improvement in the country’s international trade competitiveness, and meanwhile a new variable is added to the models to represent the portfolio’s sensitivity to excess returns on the governance portfolio (BIST Governance) over the market. Some robust and Bayesian linear models have been derived using the monthly capital gains between December 2009 and December 2019 of four leading index portfolios. A crude measure is then introduced that we think can be used in assessing governance quality of portfolios. This is called governance quality score (GQS). Our robust regression findings suggest both superiority of conditional models assuming varying beta coefficients over static model proposals and significant impact of corporate governance quality on portfolio returns. The Bayesian model proposals, however, exhibited robust findings that favor the static model with fixed beta estimates and were lacking in supporting significance of corporate governance quality.


Econometrics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 26
Author(s):  
Jennifer L. Castle ◽  
Jurgen A. Doornik ◽  
David F. Hendry

We investigate forecasting in models that condition on variables for which future values are unknown. We consider the role of the significance level because it guides the binary decisions whether to include or exclude variables. The analysis is extended by allowing for a structural break, either in the first forecast period or just before. Theoretical results are derived for a three-variable static model, but generalized to include dynamics and many more variables in the simulation experiment. The results show that the trade-off for selecting variables in forecasting models in a stationary world, namely that variables should be retained if their noncentralities exceed unity, still applies in settings with structural breaks. This provides support for model selection at looser than conventional settings, albeit with many additional features explaining the forecast performance, and with the caveat that retaining irrelevant variables that are subject to location shifts can worsen forecast performance.


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