Aqua­{μ-N-[3-(dimethyl­amino)­prop­yl]-N′-(2-oxidophen­yl)oxamidato(3−)}(1,10-phenanthroline)dicopper(II) nitrate

The title complex, [Cu2(C13H16N3O3)(C12H8N2)(H2O)]NO3, consists of a nitrate ion and a binuclear CuII unit in which the oxamide ligand has a cis geometry, is fully deprotonated and acts in a bidentate fashion to one CuII atom and in a tetradentate fashion to the other CuII atom. The CuII atom coordination geometries are distorted square-planar and distorted square-pyramidal. In the crystal structure, binuclear complexes and nitrate ions are connected by classical O—H⋯O and non-classical C—H⋯O hydrogen bonds into a three-dimensional framework. The alkyl chains of the anion are equally disorded over two positions

Towards Boosting Many-to-Many Multilingual Machine Translation with Large Language Models

The training paradigm for machine translation has gradually shifted, from learning neural machine translation (NMT) models with extensive parallel corpora to instruction finetuning on multilingual large language models (LLMs) with high-quality translation pairs. In this paper, we focus on boosting many-to-many multilingual translation of LLMs with an emphasis on zero-shot translation directions. We demonstrate that prompt strategies adopted during finetuning are crucial to zero-shot translation and introduce a cross-lingual consistency regularization, XConST, to bridge the representation gap among different languages and improve zero-shot translation performance. XConST is not a new method, but a version of CrossConST (Gao et al., 2023a) adapted for translation instruction finetuning with LLMs. Experimental results on ALMA (Xu et al., 2023), Tower (Team, 2024), and LLaMA-2 (Touvron et al., 2023) show that our approach consistently improves translation performance. Our implementations are available at https://github.com/gpengzhi/CrossConST-LLM

[N′-(3-Meth­oxy-2-oxidobenzyl­idene)nicotinohydrazidato]dimethyl­tin(IV)

In the title complex, [Sn(CH3)2(C14H11N3O3)], the Sn atom is in a distorted trigonal-bipyramidal coordination, with Sn—O distances of 2.138 (2) and 2.176 (2) Å. The dihedral angles between the two chelated benzene rings and the O—Sn—N group are 71.73 (9) and 83.30 (9)°

Modeling Coherence for Discourse Neural Machine Translation

Discourse coherence plays an important role in the translation of one text. However, the previous reported models most focus on improving performance over individual sentence while ignoring cross-sentence links and dependencies, which affects the coherence of the text. In this paper, we propose to use discourse context and reward to refine the translation quality from the discourse perspective. In particular, we generate the translation of individual sentences at first. Next, we deliberate the preliminary produced translations, and train the model to learn the policy that produces discourse coherent text by a reward teacher. Practical results on multiple discourse test datasets indicate that our model significantly improves the translation quality over the state-of-the-art baseline system by +1.23 BLEU score. Moreover, our model generates more discourse coherent text and obtains +2.2 BLEU improvements when evaluated by discourse metrics.Comment: Accepted by AAAI201

Design and development of infrastructure of the Dome A Kunlun Station (2005–2015)

To enable further advanced study of Antarctica, a new station called Kunlun Station has been built by China in the Dome A region of the inland East Antarctic ice sheet. This paper describes the Antarctic station building design system that was developed with consideration of factors that may affect Kunlun Station, such as environment and climate, construction work and transport, environmental protection and energy conservation, psychological requirements and functional requirements. The design system included site selection, station planning, external building form, construction work, function and indoor environment, energy conservation, environmental protection, and material strategy. We also describe the experience acquired during the transportation and construction phases of Kunlun Station