Zeta-like Multizeta Values for higher genus curves

We prove or conjecture several relations between the multizeta values for positive genus function fields of class number one, focusing on the zeta-like values, namely those whose ratio with the zeta value of the same weight is rational (or conjecturally equivalently algebraic). These are the first known relations between multizetas, which are not with prime field coefficients. We seem to have one universal family. We also find that interestingly the mechanism with which the relations work is quite different from the rational function field case, raising interesting questions about the expected motivic interpretation in higher genus. We provide some data in support of the guesses.Comment: Expository revisions plus appendices containing proofs of more cases of conjecture

El impacto de la formación en línea en la transferencia de comportamiento y en el desempeño laboral en una gran organización

Este estudio analiza la efectividad de la formación en línea en una gran organización. Se ha probado la influencia de diferentes procesos de la formación, como las estrategias de aprendizaje, las reacciones, el apoyo a la transferencia y las barreras, en la transferencia del comportamiento y el desempeño laboral. Los participantes fueron 3,600 empleados de un banco público brasileño que participaron en una formación en línea en el trabajo. Seis meses después, sus supervisores evaluaron las influencias de la formación en el comportamiento laboral de sus subordinados. Los hallazgos indicaron que en la autoevaluación la transferencia del comportamiento se predijo mediante estrategias de aprendizaje de elaboración/aplicación práctica, reacciones a la formación, apoyo organizacional y de pares; las estrategias de control de la motivación, cognitivas/búsqueda de ayuda y elaboración/aplicación práctica, junto con las reacciones a la formación, se relacionaron significativamente con el desempeño laboral. En la heteroevaluación, el apoyo del supervisor contribuyó a explicar la transferencia del comportamiento y las estrategias cognitivas/búsqueda de ayuda explicaron el desempeño laboral. Se identificó el papel mediador de las reacciones a la formación y el apoyo a la transferencia mostró efectos moderadores marginales.This study analyzes the effectiveness of online training in a large organization. We tested the influence of different training processes, such as learning strategies, reactions, support of transfer, and barriers, on behavioral transfer and job performance. The participants were 3,600 employees of a Brazilian public bank after taking part in online training at work. Six months later, their supervisors evaluated the influences of the training on their subordinates’ work behaviors. Findings indicated that in self-evaluation behavioral transfer was predicted by elaboration/practical application learning strategies, trainees’ reactions to training, organizational, and peer support; motivation control, cognitive/help-seeking, and elaboration/practical application learning strategies, along with trainees’ reactions to training, were significantly related to job performance. In hetero-evaluation, supervisor support contributed to explaining behavioral transfer, and cognitive/help-seeking strategies explained job performance. The mediating role of reactions to training was identified, and support of transfer showed marginal moderating effects.Ministerio de Economía y Competitividad PSI2015-64894-

Evolving Aesthetic Maps for a Real Time Strategy Game

Artículo publicado en congreso SEED'2013 (I Spanish Symposium on Entertainment Computing), Septiembre 2013, Madrid.This paper presents a procedural content generator method that have been able to generate aesthetic maps for a real-time strategy game. The maps has been characterized based on several of their properties in order to de ne a similarity function between scenarios. This function has guided a multi-objective evolution strategy during the process of generating and evolving scenarios that are similar to other aesthetic maps while being di erent to a set of non-aesthetic scenarios. The solutions have been checked using a support-vector machine classi er and a self-organizing map obtaining successful results (generated maps have been classi ed as aesthetic maps)

Performance Evaluation of cuDNN Convolution Algorithms on NVIDIA Volta GPUs

Convolutional neural networks (CNNs) have recently attracted considerable attention due to their outstanding accuracy in applications, such as image recognition and natural language processing. While one advantage of the CNNs over other types of neural networks is their reduced computational cost, faster execution is still desired for both training and inference. Since convolution operations pose most of the execution time, multiple algorithms were and are being developed with the aim of accelerating this type of operations. However, due to the wide range of convolution parameter configurations used in the CNNs and the possible data type representations, it is not straightforward to assess in advance which of the available algorithms will be the best performing in each particular case. In this paper, we present a performance evaluation of the convolution algorithms provided by the cuDNN, the library used by most deep learning frameworks for their GPU operations. In our analysis, we leverage the convolution parameter configurations from widely used the CNNs and discuss which algorithms are better suited depending on the convolution parameters for both 32 and 16-bit floating-point (FP) data representations. Our results show that the filter size and the number of inputs are the most significant parameters when selecting a GPU convolution algorithm for 32-bit FP data. For 16-bit FP, leveraging specialized arithmetic units (NVIDIA Tensor Cores) is key to obtain the best performance.This work was supported by the European Union's Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie under Grant 749516, and in part by the Spanish Juan de la Cierva under Grant IJCI-2017-33511Peer ReviewedPostprint (published version

Learning strategies scale: adaptation to Portuguese and factor structure

Since learning strategies seem to be an important set of variables to explain the effectiveness of training and e-learning in organizations is here to stay, this paper aimed to analyze the factor structure and psychometric properties of a Learning Strategies Scale (LSS) and its relationship with the training transfer in an e-learning corporate context. A total of 3600 employees of a Brazilian bank participated in this study by responding to the LSS after taking part in an online course. We measured training transfer with self-evaluation and hetero-evaluation scales. Internal consistency, confirmatory factor analysis, and multiple regressions were conducted. A four-factor structure and an acceptable level of fit for the model were found. All types of learning strategies were related to training transfer in self-evaluation, and the cognitive and help-seeking strategies contributed to explain training transfer in hetero-evaluation. As a reliable and valid measure that predicts the effectiveness of training and job performance, participants should be advised about the learning strategies that produce better performance results at the workplace. Future research should use it in different contexts and samples, analyzing its relationships with other workplace variables.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior” (CAPES/Brazil

Self interest and justice principle

We introduce non-enforceable property rights over bargaining surplus in a dictator game with production, in which the effort of the agents is differentially rewarded. Using experimental data we elicit individual preferences over the egalitarian, the accountability and the libertarian principle and provide evidence to support the inability of these justice principles to account for the observed behavior. Although this finding is consistent with the idea of individuals interpreting justice principles differently, we show that dictators behave self-interested concerning redistribution and choose which justice principle best maximizes their own payoff. We interpret this result as the justice norm imposing a constraint on otherwise self-maximizing agents.dictator game, justice principles, self-interest, self-serving bias.