Atomic Structure-free Representation of Active Motifs for Expedited Catalyst Discovery

For CO* and H* binding energy prediction, we develop new representation of catalyst surface which split surface into three types of site, first nearest neighbor of adsorbates and second nearest neighbor in same layer and sublayer. From this representation and machine learning regression model, we achieve reasonable accuracy (0.120 eV for CO* and 0.105 eV for H*) with quick training (~200 sec using CPU). Because our representation does not require density functional calculation and atomic structure modelling, it can predict binding energies of possible active motifs without time-consuming steps.

Atomic Structure-free Representation of Active Motifs for Expedited Catalyst Discovery

For CO* and H* binding energy prediction, we develop new representation of catalyst surface which split surface into three types of site, first nearest neighbor of adsorbates and second nearest neighbor in same layer and sublayer. From this representation and machine learning regression model, we achieve reasonable accuracy (0.120 eV for CO* and 0.105 eV for H*) with quick training (~200 sec using CPU). Because our representation does not require density functional calculation and atomic structure modelling, it can predict binding energies of possible active motifs without time-consuming steps.

Atomic Structure-free Representation of Active Motifs for Expedited Catalyst Discovery

For CO* and H* binding energy prediction, we develop new representation of catalyst surface which split surface into three types of site, first nearest neighbor of adsorbates and second nearest neighbor in same layer and sublayer. From this representation and machine learning regression model, we achieve reasonable accuracy (0.120 eV for CO* and 0.105 eV for H*) with quick training (~200 sec using CPU). Because our representation does not require density functional calculation and atomic structure modelling, it can predict binding energies of possible active motifs without time-consuming steps.

BUROCRACIA COM DEMOCRACIA: A ADMINISTRAÇÃO BUROCRÁTICA-COLEGIADA-PARTILHADA COM SISTEMA DE REPRESENTAÇÃO-LIVRE SEGUNDO MAX WEBER BUREAUCRACY WITH DEMOCRACY: THE BUREAUCRATIC-COLLEGIATE ADMINISTRATION WITH FREE-REPRESENTATION SYSTEM ACCORDING TO MAX WEBER

O artigo analisa os dois tipos ideais de burocracia em Max Weber, a “administração burocrática monocrática” e a “administração burocrática colegiada com representação livre”. Ambos os tipos são apresentados por Max Weber em lugares separados do capítulo sobre a dominação, redigido na fase tardia de Economia e Sociedade. A análise comparativo-sistemática dessas duas variantes da administração burocrática demonstra que, do ponto de vista histórico-exegético, Max Weber buscava integrar analiticamente o tema da democracia no contexto de sua sociologia da dominação. A partir de tal constatação sugere-se uma leitura diferenciada de sua teoria política que explora, além das tensões e contradições, também os nexos estruturais existentes entre a forma racional de dominação e a democracia.ABSTRACTThe article analyzes the two ideal types of bureaucracy in Max Weber, the “monocratic bureaucratic administration” and the “collegiate bureaucratic administration with free representation. Both types are presented by Max Weber in separate places from the chapter on domination written in the late phase of Economics and Society. The comparative-systematic analysis of these two variants of bureaucratic administration demonstrates that, from a historical-exegetical point of view, Max Weber sought to analytically integrate the theme of democracy into the context of hissociology of domination. Based on this observation, a differentiated reading of his political theory is suggested, which explores, in addition to the tensions and contradictions, also the existing structural links between the rational form of domination and the democracy.

Discrete Wavelet Packet Transform Based Discriminant Analysis for Whole Genome Sequences

In recent years, alignment-free methods have been widely applied in comparing genome sequences, as these methods compute efficiently and provide desirable phylogenetic analysis results. These methods have been successfully combined with hierarchical clustering methods for finding phylogenetic trees. However, it may not be suitable to apply these alignment-free methods directly to existing statistical classification methods, because an appropriate statistical classification theory for integrating with the alignment-free representation methods is still lacking. In this article, we propose a discriminant analysis method which uses the discrete wavelet packet transform to classify whole genome sequences. The proposed alignment-free representation statistics of features follow a joint normal distribution asymptotically. The data analysis results indicate that the proposed method provides satisfactory classification results in real time.

Family of Enneper Minimal Surfaces

We consider a family of higher degree Enneper minimal surface E m for positive integers m in the three-dimensional Euclidean space E 3 . We compute algebraic equation, degree and integral free representation of Enneper minimal surface for m = 1 , 2 , 3 . Finally, we give some results and relations for the family E m .