Titlebook: Limits of Democracy; From the June 2013 U Marcos Nobre Book 2022 The Editor(s) (if applicable) and The Author(s), under exclusive license t

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Dissonance

, Coalition Presidentialism, and the Crisis of Democracy,se to exist if theory failed to explain how it works. Examining the case of Brazil, it contrasts the explanatory thesis of . with other theses that have similar objectives, especially the one that is conventionally called coalition presidentialism. It is a starting point that establishes the underst

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BANAL

,From the “New Rights” to Bolsonaro’s Election in 2018,rights,” and the shorter one the institutional environment that has collapsed since 2013. To do so, it begins by properly distinguishing terms that are usually amalgamated: “June 2013,” “new rights,” “Bolsonaro,” “..” This starting point should enable the reconstruction of Bolsonaro’s presidential c

炸壞

The Bolsonaro Government as the Limit Form of ,y of Bolsonaro’s social and electoral support base over time. It also addresses the question of the relationship between Bolsonaro’s specific style of governing and process of coadapting his authoritarian project to destroy democratic institutions, with the political system’s self-protection interes

dura-mater

s. The complexity of nonlinear regression techniques is gradually expanding with the development of analytical and experimental techniques; hence model structure and parameter identification is a current and important topic in the field of nonlinear regression, not just from a scientific but also fr

不理會

Marcos Nobres. The complexity of nonlinear regression techniques is gradually expanding with the development of analytical and experimental techniques; hence model structure and parameter identification is a current and important topic in the field of nonlinear regression, not just from a scientific but also fr

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OMIT

Marcos Nobrely-used unsure nodule data such as LIDC-IDRI, we constructed a sure nodule data with gold-standard clinical diagnosis. To make the traditional CNN networks interpretable, we propose herewith a novel collaborative model to improve the trustworthiness of lung cancer predictions by self-regulation, whi

小步舞

Marcos Nobreconstrained by features that are pre-defined by human semantics. A down-side is that it is difficult to understand the rationale of the model predictions and to identify potential failure modes. This is a major barrier to adoption of deep learning in clinical practice. In this paper we ask if two ex