Augmenting Large Language Model Translators via Translation Memories

Using translation memories (TMs) as prompts is a promising approach to in-context learning of machine translation models. In this work, we take a step towards prompting large language models (LLMs) with TMs and making them better translators. We find that the ability of LLMs to ``understand'' prompts is indeed helpful for making better use of TMs. Experiments show that the results of a pre-trained LLM translator can be greatly improved by using high-quality TM-based prompts. These results are even comparable to those of the state-of-the-art NMT systems which have access to large-scale in-domain bilingual data and are well tuned on the downstream tasks.Comment: Accepted to Findings of ACL 202

Figure 1 in Influence of CO -induced seawater acidification on the development and lifetime reproduction of Tigriopus japonicus Mori, 1938

Figure 1. Effect of carbon dioxide (CO2)-induced seawater acidification on development time [mean ± standard deviation (SD), N = 3] of Tigriopus japonicus (N–C, nauplius to copepodite; C–A, copepodite to adult).Published as part of Cao, Zhiquan, Mu, Fanghong, Wei, Xiaohui & Sun, Yantao, 2015, Influence of CO -induced seawater acidification on the development and lifetime reproduction of Tigriopus japonicus Mori, 1938, pp. 2813-2826 in Journal of Natural History 49 (45) on page 2818, DOI: 10.1080/00222933.2015.1034213, http://zenodo.org/record/400224

A Comprehensive Survey on Geometric Deep Learning

Deep learning methods have achieved great success in analyzing traditional data such as texts, sounds, images and videos. More and more research works are carrying out to extend standard deep learning technologies to geometric data such as point cloud or voxel grid of 3D objects, real life networks such as social and citation network. Many methods have been proposed in the research area. In this work, we aim to provide a comprehensive survey of geometric deep learning and related methods. First, we introduce the relevant knowledge and history of geometric deep learning field as well as the theoretical background. In the method part, we review different graph network models for graphs and manifold data. Besides, practical applications of these methods, datasets currently available in different research area and the problems and challenges are also summarized

Effect of simulated ocean acidification on the acute toxicity of Cu and Cd to Tigriopus japonicus

Heavy metals pollution in marine environments has caused great damage to marine biological and ecological systems. Heavy metals accumulate in marine creatures, after which they are delivered to higher trophic levels of marine organisms through the marine food chain, which causes serious harm to marine biological systems and human health. Additionally, excess carbon dioxide in the atmosphere has caused ocean acidification. Indeed, about one third of the CO2 released into the atmosphere by anthropogenic activities since the beginning of the industrial revolution has been absorbed by the world's oceans, which play a key role in moderating climate change. Modeling has shown that, if current trends in CO2 emissions continue, the average pH of the ocean will reach 7.8 by the end of this century, corresponding to 0.5 units below the pre-industrial level, or a three-fold increase in H+ concentration. The ocean pH has not been at this level for several millions of years. Additionally, these changes are occurring at speeds 100 times greater than ever previously observed. As a result, several marine species, communities and ecosystems might not have time to acclimate or adapt to these fast changes in ocean chemistry. In addition, decreasing ocean pH has the potential to seriously affect the growth, development and reproduction reproductive processes of marine organisms, as well as threaten normal development of the marine ecosystem. Copepods are an important part of the meiofauna that play an important role in the marine ecosystem. Pollution of the marine environment can influence their growth and development, as well as the ecological processes they are involved in. Accordingly, there is important scientific value to investigation of the response of copepods to ocean acidification and heavy metals pollution. In the present study, we evaluated the effects of simulated future ocean acidification and the toxicological interaction between ocean acidity and heavy metals of Cu and Cd on T. japonicus. To accomplish this, harpacticoids were exposed to Cu and Cd concentration gradient seawater that had been equilibrated with CO2 and air to reach pH 8.0, 7.7, 7.3 and 6.5 for 96 h. Survival was not significantly suppressed under single sea water acidification, and the final survival rates were greater than 93% in both the experimental groups and the controls. The toxicity of Cu to T. japonicus was significantly affected by sea water acidification, with the 96h LC50 decreasing by nearly threefold from 1.98 to 0.64 mg/L with decreasing pH. The 96 h LC50 of Cd decreased with decreasing pH, but there was no significant difference in mortality among pH treatments. The results of the present study demonstrated that the predicted future ocean acidification has the potential to negatively affect survival of T. japonicus by exacerbating the toxicity of Cu. The calculated safe concentrations of Cu were 11.9 (pH 7.7) and 10.5 (pH 7.3) µg/L, which were below the class I value and very close to the class II level of the China National Quality Standard for Sea Water. Overall, these results indicate that the Chinese coastal sea will face

Figure 6 in Influence of CO -induced seawater acidification on the development and lifetime reproduction of Tigriopus japonicus Mori, 1938

Figure 6. Variation in number of nauplii [mean ± standard deviation (SD), N = 3] produced by Tigriopus japonicus females over successive broods at four pH levels.Published as part of Cao, Zhiquan, Mu, Fanghong, Wei, Xiaohui & Sun, Yantao, 2015, Influence of CO -induced seawater acidification on the development and lifetime reproduction of Tigriopus japonicus Mori, 1938, pp. 2813-2826 in Journal of Natural History 49 (45) on page 2822, DOI: 10.1080/00222933.2015.1034213, http://zenodo.org/record/400224

Design and Characteristic Analysis of a Novel Bearingless SRM considering Decoupling between Torque and Suspension Force

A Bearingless Switched Reluctance Motor (BSRM) has a complicated character of nonlinear coupling; therefore, it is a hard work to operate BSRM stably. In this paper, a new type of BSRMs with novel rotor structure is proposed by analyzing relationships between motor structure and theoretical formulae of levitation force and torque. The stator structure of this new motor is same as that of traditional BSRM and each stator pole can coil one winding or two windings, while the pole arc of rotor is wider. In order to analyze the characteristics of the proposed BSRM, finite-element (FE) models are used and a 12/4 one-set-winding BSRM and a 12/8 two-sets-windings BSRM are taken as examples. The analysis results indicate that the new scheme is effective for a stable levitation. It can realize decoupling control of torque and radial force, thus simplifying its control strategy and improving the use ratio of winding currents. A control system is designed for the 12/8 BSRM based on deducing its mathematical model. Compared with traditional BSRM, the proposed scheme is easier to be implemented