Semi-Autoregressive Neural Machine Translation

Existing approaches to neural machine translation are typically autoregressive models. While these models attain state-of-the-art translation quality, they are suffering from low parallelizability and thus slow at decoding long sequences. In this paper, we propose a novel model for fast sequence generation --- the semi-autoregressive Transformer (SAT). The SAT keeps the autoregressive property in global but relieves in local and thus is able to produce multiple successive words in parallel at each time step. Experiments conducted on English-German and Chinese-English translation tasks show that the SAT achieves a good balance between translation quality and decoding speed. On WMT'14 English-German translation, the SAT achieves 5.58$\times$ speedup while maintains 88\% translation quality, significantly better than the previous non-autoregressive methods. When produces two words at each time step, the SAT is almost lossless (only 1\% degeneration in BLEU score).Comment: EMNLP 201

The Effect of Virtual Team Characteristics in Co-creation on the Quality of UGC Videos

Co-creation is a newly emerging video production method on the UGC video platform. Based on the transactive memory systems and social capital theory, this paper describes the characteristics of the virtual team formed in the co-creation, and further explores the influence of virtual team characteristics and member characteristics on video quality. This paper collects 49,785 Bilibili co-creation video data, and uses natural language processing methods and quantitative analysis methods to carry out empirical research. The study found that the specialization of virtual teams has an inverted U-shaped impact on video quality, while coordination has a positive impact and credibility has a negative impact. Additionally, the trendiness and fame of team members can enhance the inverted U-shaped impact of specialization, and fame also enhance the impact of coordination. The research results provide theoretical support for creators and managers to optimize the co-creation mode on UGC platforms

Microwave-assisted Acid-catalyzed Hydrolysis of Hemicelluloses in Rice Husk into Xylose

The development of an environmentally benign process for the hydrolysis of hemicelluloses into xylose could be one of the key technologies for making full use of biomass in the future. This paper studies dilute acid hydrolysis of hemicelluloses in rice husk (RH) into xylose using microwave radiation. Fourier transform infrared-attenuated total reflection spectroscopy was employed to quantitatively analyze xylose. The influences of hydrolysis parameters such as temperature, time, acid concentration, and ratio of RH to sulfuric acid on the yield of xylose in acid hydrolysis of RH were also investigated. The optimum hydrolysis conditions of hemicelluloses in RH to xylose are as follows: 4 wt% of H2SO4 concentration, 150 °C hydrolysis temperature, 25 min reaction time, and 1:7 ratio of RH (g) to H2SO4 (mL). Under optimum hydrolysis conditions, a yield of 32.96% xylose is obtained

The neural correlates of apathy in the context of aging and brain disorders: a meta-analysis of neuroimaging studies

IntroductionApathy is a prevalent mood disturbance that occurs in a wide range of populations, including those with normal cognitive aging, mental disorders, neurodegenerative disorders and traumatic brain injuries. Recently, neuroimaging technologies have been employed to elucidate the neural substrates underlying brain disorders accompanying apathy. However, the consistent neural correlates of apathy across normal aging and brain disorders are still unclear.MethodsThis paper first provides a brief review of the neural mechanism of apathy in healthy elderly individuals, those with mental disorders, neurodegenerative disorders, and traumatic brain injuries. Further, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, the structural and functional neuroimaging meta-analysis using activation likelihood estimation method is performed on the apathy group with brain disorders and the healthy elderly, aiming at exploring the neural correlates of apathy.ResultsThe structural neuroimaging meta-analysis showed that gray matter atrophy is associated with apathy in the bilateral precentral gyrus (BA 13/6), bilateral insula (BA 47), bilateral medial frontal gyrus (BA 11), bilateral inferior frontal gyrus, left caudate (putamen) and right anterior cingulate, while the functional neuroimaging meta-analysis suggested that the functional connectivity in putamen and lateral globus pallidus is correlated with apathy.DiscussionThrough the neuroimaging meta-analysis, this study has identified the potential neural locations of apathy in terms of brain structure and function, which may offer valuable pathophysiological insights for developing more effective therapeutic interventions for affected patients

Chronic Alcohol Causes Alteration of Lipidome Profiling in Brain

Much efforts have been tried to clarify the molecular mechanism of alcohol-induced brain damage from the perspective of genome and protein; however, the effect of chronic alcohol exposure on global lipid profiling of brain is unclear. In the present study, by using Q-TOF/MS-based lipidomics approach, we investigated the comprehensive lipidome profiling of brain from the rats orally administrated with alcohol daily, continuously for one year. Through systematically analysis of all lipids in prefrontal cortex (PFC) and striatum region, we found that long-term alcohol exposure profoundly modified brain lipidome profiling. Notably, three kinds of lipid classes, glycerophospholipid (GP), glycerolipid (GL) and fatty acyls (FA), were significantly increased in these two brain regions. Interestingly, most of the modified lipids were involved in synthetic pathways of endoplasmic reticulum (ER), which may result in ER stress-related metabolic disruption. Moreover, alcohol-modified lipid species displayed long length of carbon chain with high degree of unsaturation. Taken together, our results firstly present that chronic alcohol exposure markedly modifies brain lipidomic profiling, which may activate ER stress and eventually result in neurotoxicity. These findings provide a new insight into the mechanism of alcohol-related brain damage.Peer reviewe

Exploiting Multiple Embeddings for Chinese Named Entity Recognition

Identifying the named entities mentioned in text would enrich many semantic applications at the downstream level. However, due to the predominant usage of colloquial language in microblogs, the named entity recognition (NER) in Chinese microblogs experience significant performance deterioration, compared with performing NER in formal Chinese corpus. In this paper, we propose a simple yet effective neural framework to derive the character-level embeddings for NER in Chinese text, named ME-CNER. A character embedding is derived with rich semantic information harnessed at multiple granularities, ranging from radical, character to word levels. The experimental results demonstrate that the proposed approach achieves a large performance improvement on Weibo dataset and comparable performance on MSRA news dataset with lower computational cost against the existing state-of-the-art alternatives.Comment: accepted at CIKM 201