Ikuya Yamada

We have investigated the structural, magnetic, and electric properties of ferromagnetic ${\mathrm{BiMnO}}_{3}$ with a highly distorted perovskite structure. At ${T}_{E}=750--770\mathrm{K},$ a centrosymmetric--to--non-centrosymmetric structural transition takes place, which describes of the ferroelectricity in the system. The changes in the dielectric constant were induced by the magnetic ordering ${(T}_{M}\ensuremath{\approx}100\mathrm{K})$ as well as by the application of magnetic fields near ${T}_{M}.$ These features are attributed to the inherent coupling between the ferroelectric and ferromagnetic orders in the multiferroic system.

Entity representations are useful in natural language tasks involving entities. In this paper, we propose new pretrained contextualized representations of words and entities based on the bidirectional transformer The proposed model treats words and entities in a given text as independent tokens, and outputs contextualized representations of them. Our model is trained using a new pretraining task based on the masked language model of BERT (Devlin et al., 2019). The task involves predicting randomly masked words and entities in a large entity-annotated corpus retrieved from Wikipedia. We also propose an entity-aware self-attention mechanism that is an extension of the self-attention mechanism of the transformer, and considers the types of tokens (words or entities) when computing attention scores. The proposed model achieves impressive empirical performance on a wide range of entity-related tasks. In particular, it obtains state-of-the-art results on five well-known datasets: Open Entity (entity typing), TACRED (relation classification), CoNLL-2003 (named entity recognition), ReCoRD (cloze-style question answering), and SQuAD 1.1 (extractive question answering). Our source code and pretrained representations are available at

The oxygen evolution reaction that occurs during water oxidation is of considerable importance as an essential energy conversion reaction for rechargeable metal-air batteries and direct solar water splitting. Cost-efficient ABO3 perovskites have been studied extensively because of their high activity for the oxygen evolution reaction; however, they lack stability, and an effective solution to this problem has not yet been demonstrated. Here we report that the Fe(4+)-based quadruple perovskite CaCu3Fe4O12 has high activity, which is comparable to or exceeding those of state-of-the-art catalysts such as Ba(0.5)Sr(0.5)Co(0.8)Fe(0.2)O(3-δ) and the gold standard RuO2. The covalent bonding network incorporating multiple Cu(2+) and Fe(4+) transition metal ions significantly enhances the structural stability of CaCu3Fe4O12, which is key to achieving highly active long-life catalysts.

Named Entity Disambiguation (NED) refers to the task of resolving multiple named entity mentions in a document to their correct references in a knowledge base (KB) (e.g., Wikipedia). In this paper, we propose a novel embedding method specifically designed for NED. The proposed method jointly maps words and entities into the same continuous vector space. We extend the skip-gram model by using two models. The KB graph model learns the relatedness of entities using the link structure of the KB, whereas the anchor context model aims to align vectors such that similar words and entities occur close to one another in the vector space by leveraging KB anchors and their context words. By combining contexts based on the proposed embedding with standard NED features, we achieved state-of-theart accuracy of 93.1% on the standard CoNLL dataset and 85.2% on the TAC 2010 dataset.

Bifunctional electrocatalysts for oxygen evolution/reduction reaction (OER/ORR) are desirable for the development of energy conversion technologies. It is discovered that the manganese quadruple perovskites CaMn7O12 and LaMn7O12 show bifunctional catalysis in the OER/ORR. A possible origin of the high OER activity is the unique surface structure through corner-shared planar MnO4 and octahedral MnO6 units to promote direct OO bond formations. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.